Data Engineer (GCP)

🏢 Summary: The offer is for a Data Engineer responsible for building and optimizing scalable data platforms in cloud environments, mainly on Google Cloud Platform and Azure. The role focuses on designing big data solutions, developing ETL processes, and working with distributed data processing frameworks across international projects. It includes full remote work and opportunities for continuous technical development. 🗂️ Requirements: 3-4 years of commercial programming experience, Experience with Google Cloud Platform, Strong knowledge of Python, Strong knowledge of SQL, Strong knowledge of Scala or Java or Kotlin, Experience with BigQuery, Understanding of big data storage, modeling, processing and scheduling, Experience with Apache Spark or similar framework, Experience in data modeling and data storage, Experience with automated testing, CI/CD and code review, Experience collaborating with business stakeholders, English proficiency at minimum B2 level, Proficiency in Polish 📃 Skills: Python, SQL, Scala, Java, Kotlin, GCP, BigQuery, Spark, CI/CD, Git, Azure, Databricks, Kafka, Airflow, Docker, Kubernetes, dbt, PubSub, Dataflow, Flink 🏢 Description: We’re looking for a Data Engineer ready to push boundaries and grow with us. Datumo specializes in providing Data Engineering and Cloud Computing consulting services to clients from all over the world, primarily in Western Europe, Poland and the USA. Core industries we support include e-commerce 🛒, telecommunications 📡 and life sciences 🧬. Our team consists of exceptional people whose commitment allows us to conduct highly demanding projects. Our team members tend to stick around for more than 3 years, and when a project wraps up, we don't let them go - we embark on a journey to discover exciting new challenges for them. It's not just a workplace; it's a community that grows together! Must-have: ✅ at least 3-4 years of commercial experience in programming, ✅ proven record with a cloud provider - Google Cloud Platform, ✅ strong knowledge of Python, SQL and JVM languages (Scala or Java or Kotlin), ✅ experience in BigQuery data warehousing solution, ✅ in-depth understanding of big data aspects like data storage, modeling , processing , scheduling etc., ✅ understanding of Apache Spark (or similar distributed data processing framework), ✅ data modeling and data storage experience, ✅ ensuring solution quality through automatic tests, CI/CD and code review, ✅ proven collaboration with businesses, ✅ English proficiency at min. B2 level, proficient in Polish. Nice to have: 🌟 knowledge of dbt, Docker and Kubernetes, Apache Kafka, 🌟 familiarity with Apache Airflow or similar pipeline orchestrator, 🌟 another JVM (Java/Scala/Kotlin) programming language, 🌟 experience in Machine Learning projects, 🌟 familiarity with one of BI tools: Power BI/Looker/Tableau, 🌟 willingness to share knowledge (conferences, articles, open-source projects). What’s on offer: 🔥 100% remote work, with workation opportunity, 🔥 20 free days, 🔥 onboarding with a dedicated mentor, 🔥 project switching possible after a certain period, 🔥 individual budget for training and conferences, 🔥 benefits: Medicover Private Medical Care , co-financing of the Medicover Sport card, 🔥 opportunity to learn English with a native speaker, 🔥 regular company trips and informal get-togethers. Development opportunities in Datumo: 🚀 participation in industry conferences, 🚀 establishing Datumo's online brand presence, 🚀 support in obtaining certifications (e.g. GCP, Azure, Snowflake), 🚀 involvement in internal initiatives, like building technological roadmaps, 🚀 training budget, 🚀 access to internal technological training repositories. Discover our exemplary project: 🔌 IoT data ingestion to cloud The project integrates data from edge devices into the cloud using Azure services. The platform supports data streaming via either the IoT Edge environment with Java or Python modules, or direct connection using Kafka protocol to Event Hubs. It also facilitates batch data transmission to ADLS. Data transformation from raw telemetry to structured tables is done through Spark jobs in Databricks or data connections and update policies in Azure Data Explorer. ☁️ Petabyte-scale data platform migration to Google Cloud The goal of the project is to improve scalability and performance of the data platform by transitioning over a thousand active pipelines to GCP. The main focus is on rearchitecting existing Spark applications to either Cloud Dataproc or Cloud BigQuery SQL, depending on the Client’s requirements and automate it using Cloud Composer. 📈 Data analytics platform for investing company The project centers on developing and overseeing a data platform for an asset management company focused on ESG investing. Databricks is the central component. The platform, built on Azure cloud, integrates various Azure services for diverse functionalities. The primary task involves implementing and extending complex ETL processes that enrich investment data, using Spark jobs in Scala. Integrations with external data providers, as well as solutions for improving data quality and optimizing cloud resources, have been implemented. 🛒 Realtime Consumer Data Platform The initiative involves constructing a consumer data platform (CDP) for a major Polish retail company. Datumo actively participates from the project’s start, contributing to planning the platform’s architecture. The CDP is built on Google Cloud Platform (GCP), utilizing services like Pub/Sub, Dataflow and BigQuery. Open-source tools, including a Kubernetes cluster with Apache Kafka, Apache Airflow and Apache Flink, are used to meet specific requirements. This combination offers significant possibilities for the platform. Recruitment process: 1️⃣Tech quiz - 15 minutes 2️⃣ Soft skills interview - 30 minutes 3️⃣ Technical interview - 60 minutes Find out more by visiting our website - https://www.datumo.io If you like what we do and you dream about creating this world with us - don’t wait, apply now!

🏢 Summary: The offer is for a Data Engineer role focused on designing, building, and optimizing scalable data platforms and pipelines in cloud environments. The position involves working with big data technologies, data warehousing solutions, and distributed processing frameworks across international projects. The role emphasizes high-quality delivery through automated testing, CI/CD, and close collaboration with business stakeholders. 🗂️ Requirements: Minimum 3 years of commercial programming experience, Experience with at least one cloud provider: GCP, Azure or AWS, Knowledge of JVM language (Scala or Java or Kotlin), Knowledge of Python, Knowledge of SQL, Experience with data warehousing solution: BigQuery or Snowflake or Databricks or similar, Understanding of big data concepts: storage, modeling, processing, scheduling, Experience in data modeling, Experience in data storage solutions, Experience with automated testing and CI/CD, Experience with code review practices, Experience in collaboration with business stakeholders, English proficiency at B2 level, Communicative Polish 📃 Skills: GCP, Azure, AWS, Scala, Java, Kotlin, Python, SQL, BigQuery, Snowflake, Databricks, Spark, Dataproc, CloudComposer, PubSub, Dataflow, Kafka, Airflow, Flink, Kubernetes, Docker, BigData, CI/CD, ETL 🏢 Description: We’re looking for a Data Engineer ready to push boundaries and grow with us. Datumo specializes in providing Data Engineering and Cloud Computing consulting services to clients from all over the world, primarily in Western Europe, Poland and the USA. Core industries we support include e-commerce 🛒, telecommunications 📡 and life sciences 🧬. Our team consists of exceptional people whose commitment allows us to conduct highly demanding projects. Our team members tend to stick around for more than 3 years, and when a project wraps up, we don't let them go - we embark on a journey to discover exciting new challenges for them. It's not just a workplace; it's a community that grows together! Must-have: ✅ at least 3 years of commercial experience in programming ✅ proven record with a selected cloud provider GCP (preferred), Azure or AWS ✅ good knowledge of JVM languages (Scala or Java or Kotlin), Python, SQL ✅ experience in one of data warehousing solutions: BigQuery/Snowflake/Databricks or similar ✅ in-depth understanding of big data aspects like data storage, modeling , processing , scheduling etc. ✅ data modeling and data storage experience ✅ ensuring solution quality through automatic tests, CI/CD and code review ✅ proven collaboration with businesses ✅ English proficiency at B2 level, communicative in Polish Nice to have: 🌟 knowledge of dbt, Docker and Kubernetes, Apache Kafka 🌟 familiarity with Apache Airflow or similar pipeline orchestrator 🌟 another JVM (Java/Scala/Kotlin) programming language 🌟 experience in Machine Learning projects 🌟 understanding of Apache Spark or similar distributed data processing framework 🌟 familiarity with one of BI tools: Power BI/Looker/Tableau 🌟 willingness to share knowledge (conferences, articles, open-source projects) What’s on offer: 🔥 100% remote work, with workation opportunity 🔥 20 free days 🔥 onboarding with a dedicated mentor 🔥 project switching possible after a certain period 🔥 individual budget for training and conferences 🔥 benefits: Medicover Private Medical Care , co-financing of the Medicover Sport card 🔥 opportunity to learn English with a native speaker 🔥 regular company trips and informal get-togethers Development opportunities in Datumo: 🚀 participation in industry conferences 🚀 establishing Datumo's online brand presence 🚀 support in obtaining certifications (e.g. GCP, Azure, Snowflake) 🚀 involvement in internal initiatives, like building technological roadmaps 🚀 training budget 🚀 access to internal technological training repositories Discover our exemplary project: 🔌 IoT data ingestion to cloud The project integrates data from edge devices into the cloud using Azure services. The platform supports data streaming via either the IoT Edge environment with Java or Python modules, or direct connection using Kafka protocol to Event Hubs. It also facilitates batch data transmission to ADLS. Data transformation from raw telemetry to structured tables is done through Spark jobs in Databricks or data connections and update policies in Azure Data Explorer. ☁️ Petabyte-scale data platform migration to Google Cloud The goal of the project is to improve scalability and performance of the data platform by transitioning over a thousand active pipelines to GCP. The main focus is on rearchitecting existing Spark applications to either Cloud Dataproc or Cloud BigQuery SQL, depending on the Client’s requirements and automate it using Cloud Composer. 📈 Data analytics platform for investing company The project centers on developing and overseeing a data platform for an asset management company focused on ESG investing. Databricks is the central component. The platform, built on Azure cloud, integrates various Azure services for diverse functionalities. The primary task involves implementing and extending complex ETL processes that enrich investment data, using Spark jobs in Scala. Integrations with external data providers, as well as solutions for improving data quality and optimizing cloud resources, have been implemented. 🛒 Realtime Consumer Data Platform The initiative involves constructing a consumer data platform (CDP) for a major Polish retail company. Datumo actively participates from the project’s start, contributing to planning the platform’s architecture. The CDP is built on Google Cloud Platform (GCP), utilizing services like Pub/Sub, Dataflow and BigQuery. Open-source tools, including a Kubernetes cluster with Apache Kafka, Apache Airflow and Apache Flink, are used to meet specific requirements. This combination offers significant possibilities for the platform. Recruitment process: 1️⃣Quiz - 15 minutes 2️⃣ Soft skills interview - 30 minutes 3️⃣ Technical interview - 60 minutes Find out more by visiting our website - https://www.datumo.io If you like what we do and you dream about creating this world with us - don’t wait, apply now!

🏢 Summary: Remote Mid/Senior Cloud Data Engineer role focused on building enterprise-scale data platforms and scalable batch/streaming pipelines using GCP, Azure, Snowflake, BigQuery, and Databricks. The position involves data architecture, coding, optimization, and collaboration on cloud modernization projects for large organizations. Offers flexible remote work, technical growth opportunities, and work with modern cloud and data technologies. 🗂️ Requirements: 3+ years of commercial experience in data engineering, Experience with GCP or Azure, Hands-on experience with BigQuery, Snowflake, or Databricks, Strong programming skills in Python or Java/Scala, Advanced SQL skills, Knowledge of data modeling and scalable data architecture, Experience maintaining robust data pipelines, English level B2+, Communicative Polish 📃 Skills: GCP, Azure, Snowflake, BigQuery, Databricks, Python, Java, Scala, SQL, Airflow, Kafka, dbt, Spark, Terraform, Docker, Kubernetes, CI/CD, Pub/Sub, Dataflow, Flink 🏢 Description: Mid/Senior Cloud Data Engineer (GCP / Azure / Snowflake / BigQuery) 100% Remote We are not a general software house. We focus purely on data at an enterprise scale. Salary: 20,000 - 30,000 PLN net + VAT / month Contract: B2B Location: 100% Remote (Poland-based team) About Datumo Datumo is a Big Data & Cloud company specializing in data platforms, data engineering, cloud modernization, and practical AI solutions. We don't do "everything for everyone". We focus exclusively on data. We are proud to be one of only 10 Google Cloud Managed Partners in Poland , as well as certified Azure and Snowflake Partners. Working with us means building solutions for large organizations and enterprise-scale environments, including clients like Żabka Polska, G2A, and LPP SA . 🛠️ What You Will Work On At Datumo, you will work on real data platforms, not simple reporting tasks. You will help build systems that process, transform, and serve data at scale for large organizations. Depending on the project, your mission will include: Architecture & Pipelines: Designing, building, and optimizing scalable batch and streaming data pipelines in GCP and/or Azure . Modern Data Stack: Working deeply with enterprise ecosystems like BigQuery, Snowflake, or Databricks . Coding: Writing high-quality code using Python or JVM languages ( Java/Scala ), and solving complex problems with SQL . Engineering Excellence: Improving data quality, performance, reliability, and observability, while working with orchestration, CI/CD, and infrastructure tools. Impact & Consulting: Collaborating directly with architects and client-side teams, taking an active part in technical decisions, code reviews, and helping clients move away from legacy solutions. 🎯 What We Expect (Must-Haves): Experience: 3+ years of commercial experience in data engineering. Cloud & Platform: Practical experience with at least one major cloud provider ( GCP or Azure ), as well as  hands-on experience with at least one modern data warehouse/platform ( BigQuery, Snowflake, or Databricks ). Core Skills: Strong programming skills in Python OR Java/Scala , combined with advanced SQL capabilities. Data Mastery: Deep understanding of data modeling, data quality, scalable data architecture, and maintaining robust pipelines. Communication: English at a B2+ level and communicative Polish. Nice-to-Have: Airflow; Kafka or other streaming technologies; dbt; Spark; Terraform; CI/CD experience; Docker and Kubernetes; experience with cloud cost optimization; experience in enterprise or long-term client projects; cloud certifications. Discover Our Exemplary Projects: ☁️ Petabyte-Scale GCP Migration: Rearchitecting over 1,000 active Spark pipelines to Cloud Dataproc or BigQuery SQL, fully automated with Cloud Composer, to massively improve scalability. 🛒 Realtime Consumer Data Platform: Building a CDP for a major retail company utilizing GCP (Pub/Sub, Dataflow, BigQuery) combined with open-source components like Kafka, Airflow, Flink, and Kubernetes. 📈 ESG Data Analytics Platform: Developing an Azure-based data platform for an investing company. Databricks acts as the central component for complex ETL processes (Spark/Scala) enriching investment data. What We Offer: Top Compensation: 20,000 - 30,000 PLN net + VAT / month (B2B) + 20 paid days off. Growth & Mentorship: A dedicated mentor during onboarding, a training budget, and full financial/educational support in obtaining cloud certifications. Community: Work alongside a highly specialized team of around 60 data experts - not a random project assembly. Flexibility: 100% remote work and the possibility to switch projects after some time to keep your mind sharp. Perks: Private medical care, sports package, English lessons with a native speaker, and fantastic team integrations/company trips. The Recruitment Process (Simple & Technical): We respect your time. Our process skips the fluff: Short Tech Quiz (15 min): A quick validation of your data fundamentals. Technical Conversation: A deep-dive discussion with Datumo engineers about architecture and your past projects. Final Decision & Offer. Sounds like a good fit? Apply and tell us briefly what kind of data engineering projects you have worked on!

🏢 Summary: Remote Mid/Senior Cloud Data Engineer role focused on building and optimizing enterprise-scale data platforms and pipelines using GCP, Azure, Snowflake, BigQuery, and modern data stack technologies. The position involves data architecture, streaming and batch processing, coding in Python or JVM languages, and collaboration on cloud modernization projects for large organizations. The offer includes B2B compensation, certification support, mentorship, and fully remote work within a Poland-based team. 🗂️ Requirements: 3+ years of commercial experience in data engineering, Experience with GCP or Azure, Hands-on experience with BigQuery, Snowflake, or Databricks, Programming skills in Python or Java, Programming skills in Scala, Advanced SQL skills, Understanding of data modeling, Knowledge of scalable data architecture, Experience maintaining robust data pipelines, English level B2+, Communicative Polish 📃 Skills: GCP, Azure, Snowflake, BigQuery, Databricks, Python, Java, Scala, SQL, Airflow, Kafka, dbt, Spark, Terraform, Docker, Kubernetes, CI/CD, Dataflow, Pub/Sub, Flink, Cloud, ETL 🏢 Description: Mid/Senior Cloud Data Engineer (GCP / Azure / Snowflake / BigQuery) 100% Remote We are not a general software house. We focus purely on data at an enterprise scale. Salary: 20,000 - 30,000 PLN net + VAT / month Contract: B2B Location: 100% Remote (Poland-based team) About Datumo Datumo is a Big Data & Cloud company specializing in data platforms, data engineering, cloud modernization, and practical AI solutions. We don't do "everything for everyone". We focus exclusively on data. We are proud to be one of only 10 Google Cloud Managed Partners in Poland , as well as certified Azure and Snowflake Partners. Working with us means building solutions for large organizations and enterprise-scale environments, including clients like Żabka Polska, G2A, and LPP SA . 🛠️ What You Will Work On At Datumo, you will work on real data platforms, not simple reporting tasks. You will help build systems that process, transform, and serve data at scale for large organizations. Depending on the project, your mission will include: Architecture & Pipelines: Designing, building, and optimizing scalable batch and streaming data pipelines in GCP and/or Azure . Modern Data Stack: Working deeply with enterprise ecosystems like BigQuery, Snowflake, or Databricks . Coding: Writing high-quality code using Python or JVM languages ( Java/Scala ), and solving complex problems with SQL . Engineering Excellence: Improving data quality, performance, reliability, and observability, while working with orchestration, CI/CD, and infrastructure tools. Impact & Consulting: Collaborating directly with architects and client-side teams, taking an active part in technical decisions, code reviews, and helping clients move away from legacy solutions. 🎯 What We Expect (Must-Haves): Experience: 3+ years of commercial experience in data engineering. Cloud & Platform: Practical experience with at least one major cloud provider ( GCP or Azure ), as well as  hands-on experience with at least one modern data warehouse/platform ( BigQuery, Snowflake, or Databricks ). Core Skills: Strong programming skills in Python OR Java/Scala , combined with advanced SQL capabilities. Data Mastery: Deep understanding of data modeling, data quality, scalable data architecture, and maintaining robust pipelines. Communication: English at a B2+ level and communicative Polish. Nice-to-Have: Airflow; Kafka or other streaming technologies; dbt; Spark; Terraform; CI/CD experience; Docker and Kubernetes; experience with cloud cost optimization; experience in enterprise or long-term client projects; cloud certifications. Discover Our Exemplary Projects: ☁️ Petabyte-Scale GCP Migration: Rearchitecting over 1,000 active Spark pipelines to Cloud Dataproc or BigQuery SQL, fully automated with Cloud Composer, to massively improve scalability. 🛒 Realtime Consumer Data Platform: Building a CDP for a major retail company utilizing GCP (Pub/Sub, Dataflow, BigQuery) combined with open-source components like Kafka, Airflow, Flink, and Kubernetes. 📈 ESG Data Analytics Platform: Developing an Azure-based data platform for an investing company. Databricks acts as the central component for complex ETL processes (Spark/Scala) enriching investment data. What We Offer: Top Compensation: 20,000 - 30,000 PLN net + VAT / month (B2B) + 20 paid days off. Growth & Mentorship: A dedicated mentor during onboarding, a training budget, and full financial/educational support in obtaining cloud certifications. Community: Work alongside a highly specialized team of around 60 data experts - not a random project assembly. Flexibility: 100% remote work and the possibility to switch projects after some time to keep your mind sharp. Perks: Private medical care, sports package, English lessons with a native speaker, and fantastic team integrations/company trips. The Recruitment Process (Simple & Technical): We respect your time. Our process skips the fluff: Short Tech Quiz (15 min): A quick validation of your data fundamentals. Technical Conversation: A deep-dive discussion with Datumo engineers about architecture and your past projects. Final Decision & Offer. Sounds like a good fit? Apply and tell us briefly what kind of data engineering projects you have worked on!

🏢 Summary: Remote Mid/Senior Cloud Data Engineer role focused on building and optimizing enterprise-scale data platforms and pipelines using GCP, Azure, Snowflake, BigQuery, and related technologies. The position involves scalable batch and streaming architectures, modern data stack development, and collaboration on technical decisions for large organizations. Offers high B2B compensation, full remote work, cloud certification support, and work on advanced data engineering projects. 🗂️ Requirements: 3+ years of commercial experience in data engineering, Experience with GCP or Azure, Hands-on experience with BigQuery, Snowflake, or Databricks, Strong programming skills in Python or Java/Scala, Advanced SQL skills, Understanding of data modeling and scalable data architecture, Experience maintaining robust data pipelines, English level B2+, Communicative Polish 📃 Skills: GCP, Azure, Snowflake, BigQuery, Databricks, Python, Java, Scala, SQL, Airflow, Kafka, dbt, Spark, Terraform, Docker, Kubernetes, CI/CD, Pub/Sub, Dataflow, Flink 🏢 Description: Mid/Senior Cloud Data Engineer (GCP / Azure / Snowflake / BigQuery) 100% Remote We are not a general software house. We focus purely on data at an enterprise scale. Salary: 20,000 - 30,000 PLN net + VAT / month Contract: B2B Location: 100% Remote (Poland-based team) About Datumo Datumo is a Big Data & Cloud company specializing in data platforms, data engineering, cloud modernization, and practical AI solutions. We don't do "everything for everyone". We focus exclusively on data. We are proud to be one of only 10 Google Cloud Managed Partners in Poland , as well as certified Azure and Snowflake Partners. Working with us means building solutions for large organizations and enterprise-scale environments, including clients like Żabka Polska, G2A, and LPP SA . 🛠️ What You Will Work On At Datumo, you will work on real data platforms, not simple reporting tasks. You will help build systems that process, transform, and serve data at scale for large organizations. Depending on the project, your mission will include: Architecture & Pipelines: Designing, building, and optimizing scalable batch and streaming data pipelines in GCP and/or Azure . Modern Data Stack: Working deeply with enterprise ecosystems like BigQuery, Snowflake, or Databricks . Coding: Writing high-quality code using Python or JVM languages ( Java/Scala ), and solving complex problems with SQL . Engineering Excellence: Improving data quality, performance, reliability, and observability, while working with orchestration, CI/CD, and infrastructure tools. Impact & Consulting: Collaborating directly with architects and client-side teams, taking an active part in technical decisions, code reviews, and helping clients move away from legacy solutions. 🎯 What We Expect (Must-Haves): Experience: 3+ years of commercial experience in data engineering. Cloud & Platform: Practical experience with at least one major cloud provider ( GCP or Azure ), as well as  hands-on experience with at least one modern data warehouse/platform ( BigQuery, Snowflake, or Databricks ). Core Skills: Strong programming skills in Python OR Java/Scala , combined with advanced SQL capabilities. Data Mastery: Deep understanding of data modeling, data quality, scalable data architecture, and maintaining robust pipelines. Communication: English at a B2+ level and communicative Polish. Nice-to-Have: Airflow; Kafka or other streaming technologies; dbt; Spark; Terraform; CI/CD experience; Docker and Kubernetes; experience with cloud cost optimization; experience in enterprise or long-term client projects; cloud certifications. Discover Our Exemplary Projects: ☁️ Petabyte-Scale GCP Migration: Rearchitecting over 1,000 active Spark pipelines to Cloud Dataproc or BigQuery SQL, fully automated with Cloud Composer, to massively improve scalability. 🛒 Realtime Consumer Data Platform: Building a CDP for a major retail company utilizing GCP (Pub/Sub, Dataflow, BigQuery) combined with open-source components like Kafka, Airflow, Flink, and Kubernetes. 📈 ESG Data Analytics Platform: Developing an Azure-based data platform for an investing company. Databricks acts as the central component for complex ETL processes (Spark/Scala) enriching investment data. What We Offer: Top Compensation: 20,000 - 30,000 PLN net + VAT / month (B2B) + 20 paid days off. Growth & Mentorship: A dedicated mentor during onboarding, a training budget, and full financial/educational support in obtaining cloud certifications. Community: Work alongside a highly specialized team of around 60 data experts - not a random project assembly. Flexibility: 100% remote work and the possibility to switch projects after some time to keep your mind sharp. Perks: Private medical care, sports package, English lessons with a native speaker, and fantastic team integrations/company trips. The Recruitment Process (Simple & Technical): We respect your time. Our process skips the fluff: Short Tech Quiz (15 min): A quick validation of your data fundamentals. Technical Conversation: A deep-dive discussion with Datumo engineers about architecture and your past projects. Final Decision & Offer. Sounds like a good fit? Apply and tell us briefly what kind of data engineering projects you have worked on!

🏢 Summary: Remote Mid/Senior Cloud Data Engineer role focused on building and optimizing enterprise-scale data platforms and pipelines using GCP, Azure, Snowflake, BigQuery, and modern data technologies. The position involves data architecture, scalable batch and streaming processing, software engineering, and collaboration with client-side technical teams. Offered on a B2B basis with full remote work, cloud certification support, and enterprise-level projects. 🗂️ Requirements: 3+ years of commercial experience in data engineering, Experience with GCP or Azure, Hands-on experience with BigQuery, Snowflake, or Databricks, Programming skills in Python or Java/Scala, Advanced SQL skills, Knowledge of data modeling and scalable data architecture, Experience maintaining robust data pipelines, English level B2+, Communicative Polish 📃 Skills: GCP, Azure, Snowflake, BigQuery, Databricks, Python, Java, Scala, SQL, Airflow, Kafka, dbt, Spark, Terraform, Docker, Kubernetes, CI/CD, PubSub, Dataflow, Flink 🏢 Description: Mid/Senior Cloud Data Engineer (GCP / Azure / Snowflake / BigQuery) 100% Remote We are not a general software house. We focus purely on data at an enterprise scale. Salary: 20,000 - 30,000 PLN net + VAT / month Contract: B2B Location: 100% Remote (Poland-based team) About Datumo Datumo is a Big Data & Cloud company specializing in data platforms, data engineering, cloud modernization, and practical AI solutions. We don't do "everything for everyone". We focus exclusively on data. We are proud to be one of only 10 Google Cloud Managed Partners in Poland , as well as certified Azure and Snowflake Partners. Working with us means building solutions for large organizations and enterprise-scale environments, including clients like Żabka Polska, G2A, and LPP SA . 🛠️ What You Will Work On At Datumo, you will work on real data platforms, not simple reporting tasks. You will help build systems that process, transform, and serve data at scale for large organizations. Depending on the project, your mission will include: Architecture & Pipelines: Designing, building, and optimizing scalable batch and streaming data pipelines in GCP and/or Azure . Modern Data Stack: Working deeply with enterprise ecosystems like BigQuery, Snowflake, or Databricks . Coding: Writing high-quality code using Python or JVM languages ( Java/Scala ), and solving complex problems with SQL . Engineering Excellence: Improving data quality, performance, reliability, and observability, while working with orchestration, CI/CD, and infrastructure tools. Impact & Consulting: Collaborating directly with architects and client-side teams, taking an active part in technical decisions, code reviews, and helping clients move away from legacy solutions. 🎯 What We Expect (Must-Haves): Experience: 3+ years of commercial experience in data engineering. Cloud & Platform: Practical experience with at least one major cloud provider ( GCP or Azure ), as well as  hands-on experience with at least one modern data warehouse/platform ( BigQuery, Snowflake, or Databricks ). Core Skills: Strong programming skills in Python OR Java/Scala , combined with advanced SQL capabilities. Data Mastery: Deep understanding of data modeling, data quality, scalable data architecture, and maintaining robust pipelines. Communication: English at a B2+ level and communicative Polish. Nice-to-Have: Airflow; Kafka or other streaming technologies; dbt; Spark; Terraform; CI/CD experience; Docker and Kubernetes; experience with cloud cost optimization; experience in enterprise or long-term client projects; cloud certifications. Discover Our Exemplary Projects: ☁️ Petabyte-Scale GCP Migration: Rearchitecting over 1,000 active Spark pipelines to Cloud Dataproc or BigQuery SQL, fully automated with Cloud Composer, to massively improve scalability. 🛒 Realtime Consumer Data Platform: Building a CDP for a major retail company utilizing GCP (Pub/Sub, Dataflow, BigQuery) combined with open-source components like Kafka, Airflow, Flink, and Kubernetes. 📈 ESG Data Analytics Platform: Developing an Azure-based data platform for an investing company. Databricks acts as the central component for complex ETL processes (Spark/Scala) enriching investment data. What We Offer: Top Compensation: 20,000 - 30,000 PLN net + VAT / month (B2B) + 20 paid days off. Growth & Mentorship: A dedicated mentor during onboarding, a training budget, and full financial/educational support in obtaining cloud certifications. Community: Work alongside a highly specialized team of around 60 data experts - not a random project assembly. Flexibility: 100% remote work and the possibility to switch projects after some time to keep your mind sharp. Perks: Private medical care, sports package, English lessons with a native speaker, and fantastic team integrations/company trips. The Recruitment Process (Simple & Technical): We respect your time. Our process skips the fluff: Short Tech Quiz (15 min): A quick validation of your data fundamentals. Technical Conversation: A deep-dive discussion with Datumo engineers about architecture and your past projects. Final Decision & Offer. Sounds like a good fit? Apply and tell us briefly what kind of data engineering projects you have worked on!

🏢 Summary: Remote Mid/Senior Cloud Data Engineer role focused on building and optimizing enterprise-scale data platforms and pipelines using GCP, Azure, Snowflake, BigQuery, and modern data stack technologies. The position involves scalable batch and streaming data engineering, cloud modernization, and collaboration on architecture and technical decisions. Offers B2B compensation, full remote work, cloud certification support, and work on large-scale data projects. 🗂️ Requirements: 3+ years commercial experience in data engineering, Experience with GCP or Azure, Experience with BigQuery, Snowflake, or Databricks, Strong Python, Java, or Scala programming skills, Advanced SQL skills, Knowledge of data modeling, Understanding of scalable data architecture, Experience maintaining robust data pipelines, English level B2+, Communicative Polish 📃 Skills: GCP, Azure, Snowflake, BigQuery, Databricks, Python, Java, Scala, SQL, Airflow, Kafka, dbt, Spark, Terraform, Docker, Kubernetes, CI/CD, Pub/Sub, Dataflow, Flink 🏢 Description: Mid/Senior Cloud Data Engineer (GCP / Azure / Snowflake / BigQuery) 100% Remote We are not a general software house. We focus purely on data at an enterprise scale. Salary: 20,000 - 30,000 PLN net + VAT / month Contract: B2B Location: 100% Remote (Poland-based team) About Datumo Datumo is a Big Data & Cloud company specializing in data platforms, data engineering, cloud modernization, and practical AI solutions. We don't do "everything for everyone". We focus exclusively on data. We are proud to be one of only 10 Google Cloud Managed Partners in Poland , as well as certified Azure and Snowflake Partners. Working with us means building solutions for large organizations and enterprise-scale environments, including clients like Żabka Polska, G2A, and LPP SA . 🛠️ What You Will Work On At Datumo, you will work on real data platforms, not simple reporting tasks. You will help build systems that process, transform, and serve data at scale for large organizations. Depending on the project, your mission will include: Architecture & Pipelines: Designing, building, and optimizing scalable batch and streaming data pipelines in GCP and/or Azure . Modern Data Stack: Working deeply with enterprise ecosystems like BigQuery, Snowflake, or Databricks . Coding: Writing high-quality code using Python or JVM languages ( Java/Scala ), and solving complex problems with SQL . Engineering Excellence: Improving data quality, performance, reliability, and observability, while working with orchestration, CI/CD, and infrastructure tools. Impact & Consulting: Collaborating directly with architects and client-side teams, taking an active part in technical decisions, code reviews, and helping clients move away from legacy solutions. 🎯 What We Expect (Must-Haves): Experience: 3+ years of commercial experience in data engineering. Cloud & Platform: Practical experience with at least one major cloud provider ( GCP or Azure ), as well as  hands-on experience with at least one modern data warehouse/platform ( BigQuery, Snowflake, or Databricks ). Core Skills: Strong programming skills in Python OR Java/Scala , combined with advanced SQL capabilities. Data Mastery: Deep understanding of data modeling, data quality, scalable data architecture, and maintaining robust pipelines. Communication: English at a B2+ level and communicative Polish. Nice-to-Have: Airflow; Kafka or other streaming technologies; dbt; Spark; Terraform; CI/CD experience; Docker and Kubernetes; experience with cloud cost optimization; experience in enterprise or long-term client projects; cloud certifications. Discover Our Exemplary Projects: ☁️ Petabyte-Scale GCP Migration: Rearchitecting over 1,000 active Spark pipelines to Cloud Dataproc or BigQuery SQL, fully automated with Cloud Composer, to massively improve scalability. 🛒 Realtime Consumer Data Platform: Building a CDP for a major retail company utilizing GCP (Pub/Sub, Dataflow, BigQuery) combined with open-source components like Kafka, Airflow, Flink, and Kubernetes. 📈 ESG Data Analytics Platform: Developing an Azure-based data platform for an investing company. Databricks acts as the central component for complex ETL processes (Spark/Scala) enriching investment data. What We Offer: Top Compensation: 20,000 - 30,000 PLN net + VAT / month (B2B) + 20 paid days off. Growth & Mentorship: A dedicated mentor during onboarding, a training budget, and full financial/educational support in obtaining cloud certifications. Community: Work alongside a highly specialized team of around 60 data experts - not a random project assembly. Flexibility: 100% remote work and the possibility to switch projects after some time to keep your mind sharp. Perks: Private medical care, sports package, English lessons with a native speaker, and fantastic team integrations/company trips. The Recruitment Process (Simple & Technical): We respect your time. Our process skips the fluff: Short Tech Quiz (15 min): A quick validation of your data fundamentals. Technical Conversation: A deep-dive discussion with Datumo engineers about architecture and your past projects. Final Decision & Offer. Sounds like a good fit? Apply and tell us briefly what kind of data engineering projects you have worked on!

🏢 Summary: Remote Mid/Senior Cloud Data Engineer role focused on building and optimizing enterprise-scale data platforms and pipelines using GCP, Azure, Snowflake, BigQuery, and related technologies. The position involves designing scalable batch and streaming solutions, coding in Python or JVM languages, and collaborating on cloud modernization and data architecture projects. The offer includes B2B compensation, full remote work, cloud certification support, and work on large-scale enterprise environments. 🗂️ Requirements: 3+ years of commercial experience in data engineering, Experience with GCP or Azure, Hands-on experience with BigQuery, Snowflake, or Databricks, Strong programming skills in Python, Java, or Scala, Advanced SQL skills, Knowledge of data modeling, Understanding of scalable data architecture, Experience maintaining robust data pipelines, English level B2+, Communicative Polish 📃 Skills: GCP, Azure, Snowflake, BigQuery, Databricks, Python, Java, Scala, SQL, Airflow, Kafka, dbt, Spark, Terraform, Docker, Kubernetes, CI/CD, Pub/Sub, Dataflow, Flink, Cloud, ETL 🏢 Description: Mid/Senior Cloud Data Engineer (GCP / Azure / Snowflake / BigQuery) 100% Remote We are not a general software house. We focus purely on data at an enterprise scale. Salary: 20,000 - 30,000 PLN net + VAT / month Contract: B2B Location: 100% Remote (Poland-based team) About Datumo Datumo is a Big Data & Cloud company specializing in data platforms, data engineering, cloud modernization, and practical AI solutions. We don't do "everything for everyone". We focus exclusively on data. We are proud to be one of only 10 Google Cloud Managed Partners in Poland , as well as certified Azure and Snowflake Partners. Working with us means building solutions for large organizations and enterprise-scale environments, including clients like Żabka Polska, G2A, and LPP SA . 🛠️ What You Will Work On At Datumo, you will work on real data platforms, not simple reporting tasks. You will help build systems that process, transform, and serve data at scale for large organizations. Depending on the project, your mission will include: Architecture & Pipelines: Designing, building, and optimizing scalable batch and streaming data pipelines in GCP and/or Azure . Modern Data Stack: Working deeply with enterprise ecosystems like BigQuery, Snowflake, or Databricks . Coding: Writing high-quality code using Python or JVM languages ( Java/Scala ), and solving complex problems with SQL . Engineering Excellence: Improving data quality, performance, reliability, and observability, while working with orchestration, CI/CD, and infrastructure tools. Impact & Consulting: Collaborating directly with architects and client-side teams, taking an active part in technical decisions, code reviews, and helping clients move away from legacy solutions. 🎯 What We Expect (Must-Haves): Experience: 3+ years of commercial experience in data engineering. Cloud & Platform: Practical experience with at least one major cloud provider ( GCP or Azure ), as well as  hands-on experience with at least one modern data warehouse/platform ( BigQuery, Snowflake, or Databricks ). Core Skills: Strong programming skills in Python OR Java/Scala , combined with advanced SQL capabilities. Data Mastery: Deep understanding of data modeling, data quality, scalable data architecture, and maintaining robust pipelines. Communication: English at a B2+ level and communicative Polish. Nice-to-Have: Airflow; Kafka or other streaming technologies; dbt; Spark; Terraform; CI/CD experience; Docker and Kubernetes; experience with cloud cost optimization; experience in enterprise or long-term client projects; cloud certifications. Discover Our Exemplary Projects: ☁️ Petabyte-Scale GCP Migration: Rearchitecting over 1,000 active Spark pipelines to Cloud Dataproc or BigQuery SQL, fully automated with Cloud Composer, to massively improve scalability. 🛒 Realtime Consumer Data Platform: Building a CDP for a major retail company utilizing GCP (Pub/Sub, Dataflow, BigQuery) combined with open-source components like Kafka, Airflow, Flink, and Kubernetes. 📈 ESG Data Analytics Platform: Developing an Azure-based data platform for an investing company. Databricks acts as the central component for complex ETL processes (Spark/Scala) enriching investment data. What We Offer: Top Compensation: 20,000 - 30,000 PLN net + VAT / month (B2B) + 20 paid days off. Growth & Mentorship: A dedicated mentor during onboarding, a training budget, and full financial/educational support in obtaining cloud certifications. Community: Work alongside a highly specialized team of around 60 data experts - not a random project assembly. Flexibility: 100% remote work and the possibility to switch projects after some time to keep your mind sharp. Perks: Private medical care, sports package, English lessons with a native speaker, and fantastic team integrations/company trips. The Recruitment Process (Simple & Technical): We respect your time. Our process skips the fluff: Short Tech Quiz (15 min): A quick validation of your data fundamentals. Technical Conversation: A deep-dive discussion with Datumo engineers about architecture and your past projects. Final Decision & Offer. Sounds like a good fit? Apply and tell us briefly what kind of data engineering projects you have worked on!

🏢 Summary: Full-time B2B DataOps Engineer role on a long-term project within a large-scale analytical ecosystem for a telecommunications organization. The position focuses on building and automating end-to-end data processing and deployment workflows across on-premises and Kubernetes environments using GitOps principles. You will design, deploy, and optimize scalable data pipelines while integrating DevOps and Data Engineering practices. 🗂️ Requirements: 2.5+ years commercial experience in Data Engineering, DataOps or DevOps, Strong Python programming, Experience with PySpark and Pandas, Hands-on experience with Kubernetes and containerized applications, Experience with Helm, Experience with Git-based workflows, Experience building CI/CD pipelines, Understanding of GitOps principles, Experience supporting full application lifecycle, Linux command-line proficiency, Experience with LDAP, Active Directory, RBAC and TLS, Experience working with on-premises infrastructure, Polish language proficiency, Based in Poland with valid Polish passport 📃 Skills: Python, PySpark, Pandas, Kubernetes, Helm, Git, GitLab, Jenkins, ArgoCD, CICD, GitOps, Linux, LDAP, ActiveDirectory, RBAC, TLS 🏢 Description: DataOps Engineer (Poland) 💻 Hybrid (Remote with bi-weekly onsite meetings) 🕦 Full-time ☑️ B2B (long-term project) 🌍 Working hours: Central European Time (CET) We are looking for a DataOps Engineer to join a large-scale analytical ecosystem project for a leading telecommunications organization. This role is ideal for an engineer who enjoys solving complex data challenges, building automation from development through production deployment, and working across both Data Engineering and DevOps domains. You will be responsible for designing, developing, deploying, and optimizing large-scale data processing solutions while helping onboard new datasets and automate the entire delivery lifecycle using GitOps principles. The environment combines on-premises infrastructure, Kubernetes, and modern data technologies, requiring someone who is comfortable working beyond cloud-managed solutions. Must-Have’s 2.5+ years of commercial experience in Data Engineering, DataOps, DevOps, or related roles. Strong Python programming skills, including experience with analytical frameworks such as PySpark and Pandas. Experience working with Kubernetes and containerized applications. Hands-on experience with Helm. Experience with Git-based development workflows. Experience building and maintaining CI/CD pipelines using GitLab, Jenkins, ArgoCD, or similar tools. Understanding of GitOps principles and automated deployment processes. Experience supporting the full application lifecycle from development through production deployment. Linux proficiency, including command-line usage. Experience with authentication and authorization technologies such as LDAP, Active Directory, RBAC, and TLS certificate management. Strong analytical and problem-solving skills. Strong English communication skills. Polish language proficiency. Must be based in Poland and available to attend onsite meetings every two weeks. Must hold a valid Polish passport. Comfortable working with on-premises infrastructure environments. Nice to Have Experience with Apache Kafka. Experience with OpenSearch or Elasticsearch. Experience with OpenSearch Data Prepper, dbt, Kafka Streams, or similar ingestion technologies. Familiarity with Hadoop ecosystems. Experience with Ansible. Knowledge of SRE best practices, including SLOs and Error Budgets. Familiarity with Elastic Common Schema (ECS). Familiarity with TMForum standards. Degree from a leading technical university such as University of Warsaw, Warsaw University of Technology, AGH University of Science and Technology, or PJATK. Key Responsibilities Design, develop, and maintain data pipelines running on large-scale analytical platforms. Build automated processes for onboarding datasets and integrating new data streams. Develop and maintain GitOps-driven deployment workflows. Design and implement CI/CD pipelines for data and platform services. Deploy and manage applications running on Kubernetes-based environments. Monitor, troubleshoot, and optimize data processing workloads for performance and scalability. Collaborate with stakeholders to gather requirements and translate business needs into technical solutions. Support application lifecycle management, including design, implementation, deployment, and maintenance. Improve operational efficiency through automation and infrastructure standardization. Work closely with cross-functional teams to ensure reliable and scalable platform operations. Contribute to security, governance, and operational best practices across the environment. Get to know DevsData We are a technology consulting company and a recruitment agency, delivering software solutions to clients from Europe and the US. We work 100% remotely, in an international team, including people from Asia, London, or San Francisco. We employ people with experience in international corporations as well as students of the best technical and business universities. Find out more: https://devsdata.com/

🏢 Summary: The offer is for a Software Engineer (Data) role focused on building scalable data infrastructure and production-ready ML systems within an AI-driven environment. The position combines backend engineering, data engineering, and MLOps to design high-throughput pipelines and support AI solutions from experimentation to production. The role involves close collaboration with Data Science teams to shape architecture and engineering standards for next-generation data platforms. 🗂️ Requirements: 4+ years of software engineering experience, Strong proficiency in Python, Experience building scalable production systems, Experience with data-intensive applications and SQL databases, Knowledge of data modeling and query optimization, Experience with Terraform, Kubernetes, Docker or similar tools, Understanding of CI/CD pipelines and Infrastructure as Code, Experience implementing automated testing and clean architecture principles, Ability to productionize ML solutions with Data Science teams 📃 Skills: Python, MySQL, PostgreSQL, Spark, Terraform, Kubernetes, Docker, Airflow, SQL, CI/CD, AWS, Snowflake, DBT, MLOps 🏢 Description: Our client helps small teams power big businesses with the must-have platform for intelligent marketing automation. Customers from over 170 countries depend on the Client’s mix of pre-built automation and integration to power personalized marketing, transactional emails, and one-to-one CRM interactions throughout the customer lifecycle. We’re looking for a Software Engineer (Data) to join our client’s growing AI and Data organization and help build the scalable foundations behind next-generation data and ML systems. In this role, you won’t just be working with data infrastructure; you’ll be shaping the software architecture, engineering standards, and production-ready platforms that power the company’s AI ecosystem. This is more than a traditional backend or data engineering position. You’ll work at the intersection of software engineering, data, and AI, partnering closely with Data Science and AI teams to bridge the gap between experimentation and production. From designing resilient systems to building scalable MLOps pipelines, your work will directly influence how AI solutions are developed, deployed, and scaled across the organization. Key takeaways: Stack: Python, MySQL, PostgreSQL, Spark, Terraform, Kubernetes, Docker Salary : 20 000 - 23 000 PLN gross/month, Contract of employment (+10% annual bonus, 75% Creative Tax) Working model: Hybrid, once a week in the office Location: Krakow, ul. Konopnickiej Recruitment process: Call with MOTIFE recruiter (30 min) Interview with Hiring Manager (45 min) Technical interview, live coding (1h) Cross-functional interview (1h) Responsibilities: Design, develop, and maintain scalable high-throughput data pipelines across complex data ecosystems. Build and optimize data models, schemas, and database structures to ensure long-term scalability and performance. Implement engineering best practices, including automated testing, CI/CD pipelines, and Infrastructure as Code (Terraform). Partner closely with AI and Data Science teams to productionize machine learning solutions and develop scalable MLOps pipelines. Engineer and maintain feature stores and data infrastructure supporting AI-driven initiatives. Monitor, maintain, and improve the reliability and efficiency of containerized environments using Kubernetes, Docker, and Airflow. Ensure platform stability, observability, and operational excellence through proactive system monitoring and health checks. Collaborate cross-functionally with engineering and business stakeholders to translate complex technical concepts into actionable insights. Contribute to the architectural direction and scalability of the organization’s AI and data platforms. Drive the adoption of robust software engineering standards across data and infrastructure projects. Requirements: 4+ years of experience in software engineering, with strong hands-on experience in backend development and building scalable production systems. Strong proficiency in Python and solid software engineering fundamentals, including clean architecture, testing, and maintainable code practices. Experience working with data-intensive applications, databases, and SQL, including data modeling and query optimization. Exposure to modern data engineering, cloud, or infrastructure environments, with familiarity in tools such as Terraform, Kubernetes, Docker, or similar technologies. Understanding of CI/CD pipelines, Infrastructure as Code, and general engineering best practices. Interest in AI/ML ecosystems and willingness to work closely with Data Science and AI teams on productionizing ML solutions. Familiarity with cloud platforms and modern data stack technologies such as AWS, Snowflake, Spark, or DBT is considered a strong plus. Ownership mindset and comfort working in evolving, fast-moving environments where systems and processes are still being built. What we offer: Health Benefits 1. Medical Full coverage for employees and their dependents through LUX MED. Employees have access to the “Premium” package, providing enhanced coverage and greater access to care. A client pays 100% of the premium for employees and 50% for dependents. 2. Dental No additional cost for dental coverage- integrated into LUX MED medical plan. 3. Vision Reimbursement for vision expenses up to 400 PLN every 2 years. Mental Health Tools Access to TELUS Health EAP to provide support and resources in a time of need. Additional Benefits 10% annual bonus 75% Creative Tax Vacation: 26 days. Home Office Stipend: One-time $150 equivalent home office stipend to outfit their home office. Calm Subscription: Premium subscription access to Calm, the #1 app for sleep, meditation, and relaxation. Hub Perks: Receive meal and transportation benefits when traveling to the Poland Hub. Baby Swag: If you have a baby or adopt, you’ll receive a company-branded first bath bundle. Sabbatical Program: After 5 years of employment, receive a month-long paid sabbatical leave, with a sabbatical leave bonus.