Data Engineer

🏢 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 responsible for designing and developing scalable data platforms and pipelines in cloud environments, primarily on Google Cloud Platform. The role focuses on big data processing, data modeling, and building high-quality data solutions using modern distributed frameworks. The position involves working on advanced cloud-based analytics and data warehousing projects. 🗂️ Requirements: 3-4 years commercial programming experience, Experience with Google Cloud Platform, Strong knowledge of Python, Strong knowledge of SQL, Proficiency in JVM language (Scala or Java or Kotlin), Experience with BigQuery, Understanding of big data processing and storage, Experience with Apache Spark or similar framework, Experience in data modeling, Experience with CI/CD pipelines, Experience with automated testing, Experience with code review practices 📃 Skills: Python, SQL, Scala, Java, Kotlin, GCP, BigQuery, Spark, JVM, BigData, DataModeling, CICD, Testing, CodeReview 🏢 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 (you need to be based in Poland), 🔥 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: 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: Senior Data Platform Engineer role focused on designing, building, and operating scalable, highly available data persistence systems for distributed services. The position combines backend engineering, platform reliability, and cloud-native data infrastructure to improve performance, scalability, and observability of global data ecosystems. Hybrid work model with competitive salary and comprehensive benefits. 🗂️ Requirements: 5+ years of software engineering experience in production systems, Strong backend engineering skills (Python, Java, or Kotlin), Experience with large-scale, data-intensive systems, Solid understanding of distributed systems fundamentals, Experience in cloud environments (AWS preferred), Experience with relational or NoSQL databases, Hands-on experience with large-scale data pipelines, Experience with event-driven or streaming architectures, Understanding of end-to-end data flow (ingestion, transformation, storage, access), Experience designing scalable and reliable data systems 📃 Skills: Python, Java, Kotlin, Kafka, Spark, PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch, AWS, Terraform, ETL 🏢 Description: We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere. We are looking for a Senior Data Platform Engineer to join the Datastores team. This team is responsible for building and operating the core data persistence layer used by application services across the organization. In this role, you will design and improve the systems that store, access, and scale critical data across distributed services. It is a hands-on engineering position where you will work at the intersection of backend engineering, platform reliability, and cloud-native data infrastructure. Your work will directly influence the scalability, performance, and reliability of the company’s global data ecosystem. Key takeaways: Stack: Python, Kafka, Spark, PostgreSQL, AWS Salary: 23.000 - 30 000 PLN gross per month on Employment Contract Working model: hybrid - 3x weekly from the office Location: ul. Grzybowska 60, Warsaw Recruitment process: A call with Motife recruiter (30 min) Coding Interview (1h) Interview panel: architecture & system design discussion; Hiring Manager meeting (up to 2h in total) Responsibilities: Data Infrastructure Engineering Design, build, and operate backend systems that rely on scalable and highly available data persistence layers. Contribute to architectural decisions around distributed data systems, multi-region persistence, and global scalability. Improve the reliability and performance of production datastores used by critical services. Data Performance & Optimization Partner with service teams to improve database schema design, query performance, and data modelling. Optimize data access patterns and indexing strategies for relational and NoSQL databases. Support teams in designing systems that scale efficiently under high load. Developer Experience & Platform Tooling Build and maintain self-service tooling that enables engineers to provision and manage databases and caching layers. Contribute to infrastructure automation using tools such as Terraform and internal developer platforms. Improve observability and operational insight into datastore performance and reliability. Platform Reliability & Observability Implement monitoring, metrics, and tracing strategies to improve visibility into production data systems. Develop autoscaling and performance optimization strategies for critical data infrastructure. Support operational excellence by reducing manual processes and improving system resilience. Requirements: Technical Expertise 5+ years of experience in software engineering, building and operating production systems Strong backend engineering fundamentals (e.g. Python, Java, or Kotlin) Experience working with large-scale, data-intensive systems Solid understanding of distributed systems fundamentals (e.g. scalability, latency, reliability, data consistency) Experience working in cloud environments (preferably AWS) Familiarity with relational or NoSQL databases (e.g. PostgreSQL, MySQL, DynamoDB, Redis, Elasticsearch) Data Systems & Architecture Hands-on experience with large-scale data pipelines and data processing systems Exposure to event-driven architectures, streaming or batch processing (e.g. Kafka, Spark, ETL workflows) Understanding of end-to-end data flow: ingestion (how data enters the system) transformation (how it is processed) storage & access (how other services consume it) Experience designing systems where data performance, scalability, and reliability are critical Collaboration & Engineering Mindset Ability to work cross-functionally with service teams to improve system design and data access patterns. Strong problem-solving skills with a focus on performance, scalability, and reliability. Clear communication skills and a collaborative engineering approach. What we offer: 100% paid medical care Multisport Creative tax (KUP) Home office allowance MacBook Pro Apply now If you’re excited about building developer platforms that scale, empower teams, and set new standards for engineering excellence, we’d love to hear from you. Apply via our careers page and please submit your CV in English .