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 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 / BigQuery/ Snowflake 100% Remote B2B | Poland-based team Salary range: 20,000–30,000 PLN net + VAT / month About Datumo Datumo is a Big Data & Cloud company specializing in data platforms, data engineering, cloud modernization and practical AI solutions. We work with large organizations and enterprise-scale data environments. Our clients include companies such as Żabka Polska, G2A and LPP SA. We are one of only 10 Google Cloud Managed Partners in Poland. We are also an Azure Partner and Snowflake Partner, with strong experience in GCP, Azure, Snowflake and Databricks ecosystems. We are not a general software house doing everything for everyone. We focus on data. What you will work on You will help us design, build and improve data solutions for enterprise clients. Depending on the project, your work may include: designing, building and optimizing data pipelines in GCP and/or Azure; working with BigQuery, Snowflake or Databricks; using Python or JVM languages such as Java or Scala; working with SQL in complex data environments; developing scalable batch and streaming data processing solutions; improving data quality, performance, reliability and observability; working with orchestration, CI/CD and infrastructure tools; collaborating with architects, engineers and client-side teams; taking part in technical decisions, code reviews and solution design; helping clients modernize their data platforms and move away from legacy solutions. What we expect Must-have: at least 3 years of experience in data engineering; practical experience with at least one cloud platform: GCP or Azure; hands-on experience with at least one of the following: BigQuery, Snowflake or Databricks; strong Python or Java/Scala skills; strong SQL skills; experience with building and maintaining data pipelines; understanding of data modeling, data quality and scalable data architecture; good communication skills; English at B2+ level; Polish at a communicative level. 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 data platform migration to Google Cloud Migration of 1,000+ active pipelines to GCP. Rearchitecture of Spark applications to Cloud Dataproc or BigQuery SQL. Automation with Cloud Composer. Data analytics platform for an investing company Azure-based data platform with Databricks as the central component. Complex ETL processes enriching investment data with Spark jobs in Scala. External data integrations, data quality improvements and cloud resource optimization. Realtime Consumer Data Platform Consumer Data Platform for a major Polish retail company. Architecture based on GCP services such as Pub/Sub, Dataflow and BigQuery. Open-source components including Kafka, Airflow, Flink and Kubernetes. What we offer 100% remote work; B2B; salary range: 20,000–30,000 PLN net + VAT / month; 20 days off on B2B; onboarding with a mentor; training budget; support in cloud certifications; English lessons with a native speaker; private medical care; sports package; team integrations and company trips; possibility to change projects after some time; work with experienced engineers, not a random project team; long-term Big Data and Cloud projects for large organizations. Recruitment process We keep the process simple and technical: Soft Skills Interview (30 min): A short discussion about communication and teamwork. Technical Conversation (60 min): 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 / BigQuery/ Snowflake 100% Remote B2B | Poland-based team Salary range: 20,000–30,000 PLN net + VAT / month ☁️ About Datumo Datumo is a Big Data & Cloud company specializing in data platforms, data engineering, cloud modernization and practical AI solutions. We work with large organizations and enterprise-scale data environments. Our clients include companies such as Żabka Polska, G2A and LPP SA. We are one of only 10 Google Cloud Managed Partners in Poland. We are also an Azure Partner and Snowflake Partner, with strong experience in GCP, Azure, Snowflake and Databricks ecosystems. We are not a general software house doing everything for everyone. We focus on data. 💻 What you will work on You will help us design, build and improve data solutions for enterprise clients. Depending on the project, your work may include: designing, building and optimizing data pipelines in GCP and/or Azure; working with BigQuery, Snowflake or Databricks; using Python or JVM languages such as Java or Scala; working with SQL in complex data environments; developing scalable batch and streaming data processing solutions; improving data quality, performance, reliability and observability; working with orchestration, CI/CD and infrastructure tools; collaborating with architects, engineers and client-side teams; taking part in technical decisions, code reviews and solution design; helping clients modernize their data platforms and move away from legacy solutions. 👀 What we expect Must-have: at least 3 years of experience in data engineering; practical experience with at least one cloud platform: GCP or Azure; hands-on experience with at least one of the following: BigQuery, Snowflake or Databricks; strong Python or Java/Scala skills; strong SQL skills; experience with building and maintaining data pipelines; understanding of data modeling, data quality and scalable data architecture; good communication skills; English at B2+ level; Polish at a communicative level. 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 data platform migration to Google Cloud Migration of 1,000+ active pipelines to GCP. Rearchitecture of Spark applications to Cloud Dataproc or BigQuery SQL. Automation with Cloud Composer. Data analytics platform for an investing company Azure-based data platform with Databricks as the central component. Complex ETL processes enriching investment data with Spark jobs in Scala. External data integrations, data quality improvements and cloud resource optimization. Realtime Consumer Data Platform Consumer Data Platform for a major Polish retail company. Architecture based on GCP services such as Pub/Sub, Dataflow and BigQuery. Open-source components including Kafka, Airflow, Flink and Kubernetes. ✅ What we offer 100% remote work; B2B; salary range: 20,000–30,000 PLN net + VAT / month; 20 days off on B2B; onboarding with a mentor; training budget; support in cloud certifications; English lessons with a native speaker; private medical care; sports package; team integrations and company trips; possibility to change projects after some time; work with experienced engineers, not a random project team; long-term Big Data and Cloud projects for large organizations. 📆 Recruitment process We keep the process simple and technical: Soft Skills Interview (30 min): A short discussion about communication and teamwork. Technical Conversation (60 min): 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 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 / BigQuery/ Snowflake 100% Remote B2B | Poland-based team Salary range: 20,000–30,000 PLN net + VAT / month About Datumo Datumo is a Big Data & Cloud company specializing in data platforms, data engineering, cloud modernization and practical AI solutions. We work with large organizations and enterprise-scale data environments. Our clients include companies such as Żabka Polska, G2A and LPP SA. We are one of only 10 Google Cloud Managed Partners in Poland. We are also an Azure Partner and Snowflake Partner, with strong experience in GCP, Azure, Snowflake and Databricks ecosystems. We are not a general software house doing everything for everyone. We focus on data. What you will work on You will help us design, build and improve data solutions for enterprise clients. Depending on the project, your work may include: designing, building and optimizing data pipelines in GCP and/or Azure; working with BigQuery, Snowflake or Databricks; using Python or JVM languages such as Java or Scala; working with SQL in complex data environments; developing scalable batch and streaming data processing solutions; improving data quality, performance, reliability and observability; working with orchestration, CI/CD and infrastructure tools; collaborating with architects, engineers and client-side teams; taking part in technical decisions, code reviews and solution design; helping clients modernize their data platforms and move away from legacy solutions. What we expect Must-have: at least 3 years of experience in data engineering; practical experience with at least one cloud platform: GCP or Azure; hands-on experience with at least one of the following: BigQuery, Snowflake or Databricks; strong Python or Java/Scala skills; strong SQL skills; experience with building and maintaining data pipelines; understanding of data modeling, data quality and scalable data architecture; good communication skills; English at B2+ level; Polish at a communicative level. 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 data platform migration to Google Cloud Migration of 1,000+ active pipelines to GCP. Rearchitecture of Spark applications to Cloud Dataproc or BigQuery SQL. Automation with Cloud Composer. Data analytics platform for an investing company Azure-based data platform with Databricks as the central component. Complex ETL processes enriching investment data with Spark jobs in Scala. External data integrations, data quality improvements and cloud resource optimization. Realtime Consumer Data Platform Consumer Data Platform for a major Polish retail company. Architecture based on GCP services such as Pub/Sub, Dataflow and BigQuery. Open-source components including Kafka, Airflow, Flink and Kubernetes. What we offer 100% remote work; B2B; salary range: 20,000–30,000 PLN net + VAT / month; 20 days off on B2B; onboarding with a mentor; training budget; support in cloud certifications; English lessons with a native speaker; private medical care; sports package; team integrations and company trips; possibility to change projects after some time; work with experienced engineers, not a random project team; long-term Big Data and Cloud projects for large organizations. Recruitment process We keep the process simple and technical: Soft Skills Interview (30 min): A short discussion about communication and teamwork. Technical Conversation (60 min): 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 / BigQuery/ Snowflake 100% Remote B2B | Poland-based team Salary range: 20,000–30,000 PLN net + VAT / month About Datumo Datumo is a Big Data & Cloud company specializing in data platforms, data engineering, cloud modernization and practical AI solutions. We work with large organizations and enterprise-scale data environments. Our clients include companies such as Żabka Polska, G2A and LPP SA. We are one of only 10 Google Cloud Managed Partners in Poland. We are also an Azure Partner and Snowflake Partner, with strong experience in GCP, Azure, Snowflake and Databricks ecosystems. We are not a general software house doing everything for everyone. We focus on data. What you will work on You will help us design, build and improve data solutions for enterprise clients. Depending on the project, your work may include: designing, building and optimizing data pipelines in GCP and/or Azure; working with BigQuery, Snowflake or Databricks; using Python or JVM languages such as Java or Scala; working with SQL in complex data environments; developing scalable batch and streaming data processing solutions; improving data quality, performance, reliability and observability; working with orchestration, CI/CD and infrastructure tools; collaborating with architects, engineers and client-side teams; taking part in technical decisions, code reviews and solution design; helping clients modernize their data platforms and move away from legacy solutions. What we expect Must-have: at least 3 years of experience in data engineering; practical experience with at least one cloud platform: GCP or Azure; hands-on experience with at least one of the following: BigQuery, Snowflake or Databricks; strong Python or Java/Scala skills; strong SQL skills; experience with building and maintaining data pipelines; understanding of data modeling, data quality and scalable data architecture; good communication skills; English at B2+ level; Polish at a communicative level. 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 data platform migration to Google Cloud Migration of 1,000+ active pipelines to GCP. Rearchitecture of Spark applications to Cloud Dataproc or BigQuery SQL. Automation with Cloud Composer. Data analytics platform for an investing company Azure-based data platform with Databricks as the central component. Complex ETL processes enriching investment data with Spark jobs in Scala. External data integrations, data quality improvements and cloud resource optimization. Realtime Consumer Data Platform Consumer Data Platform for a major Polish retail company. Architecture based on GCP services such as Pub/Sub, Dataflow and BigQuery. Open-source components including Kafka, Airflow, Flink and Kubernetes. What we offer 100% remote work; B2B; salary range: 20,000–30,000 PLN net + VAT / month; 20 days off on B2B; onboarding with a mentor; training budget; support in cloud certifications; English lessons with a native speaker; private medical care; sports package; team integrations and company trips; possibility to change projects after some time; work with experienced engineers, not a random project team; long-term Big Data and Cloud projects for large organizations. Recruitment process We keep the process simple and technical: Soft Skills Interview (30 min): A short discussion about communication and teamwork. Technical Conversation (60 min): 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 / BigQuery/ Snowflake 100% Remote B2B | Poland-based team Salary range: 20,000–30,000 PLN net + VAT / month About Datumo Datumo is a Big Data & Cloud company specializing in data platforms, data engineering, cloud modernization and practical AI solutions. We work with large organizations and enterprise-scale data environments. Our clients include companies such as Żabka Polska, G2A and LPP SA. We are one of only 10 Google Cloud Managed Partners in Poland. We are also an Azure Partner and Snowflake Partner, with strong experience in GCP, Azure, Snowflake and Databricks ecosystems. We are not a general software house doing everything for everyone. We focus on data. What you will work on You will help us design, build and improve data solutions for enterprise clients. Depending on the project, your work may include: designing, building and optimizing data pipelines in GCP and/or Azure; working with BigQuery, Snowflake or Databricks; using Python or JVM languages such as Java or Scala; working with SQL in complex data environments; developing scalable batch and streaming data processing solutions; improving data quality, performance, reliability and observability; working with orchestration, CI/CD and infrastructure tools; collaborating with architects, engineers and client-side teams; taking part in technical decisions, code reviews and solution design; helping clients modernize their data platforms and move away from legacy solutions. What we expect Must-have: at least 3 years of experience in data engineering; practical experience with at least one cloud platform: GCP or Azure; hands-on experience with at least one of the following: BigQuery, Snowflake or Databricks; strong Python or Java/Scala skills; strong SQL skills; experience with building and maintaining data pipelines; understanding of data modeling, data quality and scalable data architecture; good communication skills; English at B2+ level; Polish at a communicative level. 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 data platform migration to Google Cloud Migration of 1,000+ active pipelines to GCP. Rearchitecture of Spark applications to Cloud Dataproc or BigQuery SQL. Automation with Cloud Composer. Data analytics platform for an investing company Azure-based data platform with Databricks as the central component. Complex ETL processes enriching investment data with Spark jobs in Scala. External data integrations, data quality improvements and cloud resource optimization. Realtime Consumer Data Platform Consumer Data Platform for a major Polish retail company. Architecture based on GCP services such as Pub/Sub, Dataflow and BigQuery. Open-source components including Kafka, Airflow, Flink and Kubernetes. What we offer 100% remote work; B2B; salary range: 20,000–30,000 PLN net + VAT / month; 20 days off on B2B; onboarding with a mentor; training budget; support in cloud certifications; English lessons with a native speaker; private medical care; sports package; team integrations and company trips; possibility to change projects after some time; work with experienced engineers, not a random project team; long-term Big Data and Cloud projects for large organizations. Recruitment process We keep the process simple and technical: Soft Skills Interview (30 min): A short discussion about communication and teamwork. Technical Conversation (60 min): 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 / BigQuery/ Snowflake 100% Remote B2B | Poland-based team Salary range: 20,000–30,000 PLN net + VAT / month About Datumo Datumo is a Big Data & Cloud company specializing in data platforms, data engineering, cloud modernization and practical AI solutions. We work with large organizations and enterprise-scale data environments. Our clients include companies such as Żabka Polska, G2A and LPP SA. We are one of only 10 Google Cloud Managed Partners in Poland. We are also an Azure Partner and Snowflake Partner, with strong experience in GCP, Azure, Snowflake and Databricks ecosystems. We are not a general software house doing everything for everyone. We focus on data. What you will work on You will help us design, build and improve data solutions for enterprise clients. Depending on the project, your work may include: designing, building and optimizing data pipelines in GCP and/or Azure; working with BigQuery, Snowflake or Databricks; using Python or JVM languages such as Java or Scala; working with SQL in complex data environments; developing scalable batch and streaming data processing solutions; improving data quality, performance, reliability and observability; working with orchestration, CI/CD and infrastructure tools; collaborating with architects, engineers and client-side teams; taking part in technical decisions, code reviews and solution design; helping clients modernize their data platforms and move away from legacy solutions. What we expect Must-have: at least 3 years of experience in data engineering; practical experience with at least one cloud platform: GCP or Azure; hands-on experience with at least one of the following: BigQuery, Snowflake or Databricks; strong Python or Java/Scala skills; strong SQL skills; experience with building and maintaining data pipelines; understanding of data modeling, data quality and scalable data architecture; good communication skills; English at B2+ level; Polish at a communicative level. 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 data platform migration to Google Cloud Migration of 1,000+ active pipelines to GCP. Rearchitecture of Spark applications to Cloud Dataproc or BigQuery SQL. Automation with Cloud Composer. Data analytics platform for an investing company Azure-based data platform with Databricks as the central component. Complex ETL processes enriching investment data with Spark jobs in Scala. External data integrations, data quality improvements and cloud resource optimization. Realtime Consumer Data Platform Consumer Data Platform for a major Polish retail company. Architecture based on GCP services such as Pub/Sub, Dataflow and BigQuery. Open-source components including Kafka, Airflow, Flink and Kubernetes. What we offer 100% remote work; B2B; salary range: 20,000–30,000 PLN net + VAT / month; 20 days off on B2B; onboarding with a mentor; training budget; support in cloud certifications; English lessons with a native speaker; private medical care; sports package; team integrations and company trips; possibility to change projects after some time; work with experienced engineers, not a random project team; long-term Big Data and Cloud projects for large organizations. Recruitment process We keep the process simple and technical: Soft Skills Interview (30 min): A short discussion about communication and teamwork. Technical Conversation (60 min): 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: The offer is for a Data Engineer role focused on building and maintaining a large-scale, cloud-based energy market solution on Microsoft Azure. The position involves developing batch and streaming data processing pipelines using Apache Spark and Databricks within a distributed, event-driven microservices architecture. The role includes end-to-end responsibility for designing, implementing, optimizing, and maintaining scalable data solutions. 🗂️ Requirements: 4+ years of experience with Apache Spark, Experience with batch and streaming data processing, Experience with Apache Spark Structured Streaming, Experience with Apache Kafka, Experience designing technical solutions, Experience with distributed systems on cloud platforms, Experience with large-scale systems in microservices architecture, Experience with Git, Experience with CI/CD pipelines, Ability to design or implement deployment processes for data pipelines, Higher education in computer science or related field, Fluent English and Polish 📃 Skills: Spark, Databricks, Kafka, Delta, Java, SQL, Azure, Docker, Git, CI/CD, MS SQL, ElasticSearch, Redis, Azure Data Explorer, Helm, ArgoCD, GitOps, Microservices, DDD 🏢 Description: #Data Engineer #Apache Spark #Databricks #Java #Apache Kafka #Batch Processing #Structured Streaming #Azure #SQL #Microservices #CI/CD #Docker #DDD Are you ready to join our international team as a Data Engineer ? We shall tell you why you should... What product do we develop? We are building an innovative solution, KMD Elements , on Microsoft Azure cloud dedicated to the energy distribution market (electrical energy, gas, water, utility, and similar types of business). Our customers include institutions and companies operating in the energy market as transmission service operators, market regulators, distribution service operators , energy trading, and retail companies. KMD Elements delivers components allowing implementation of the full lifecycle of a customer on the energy market: meter data processing , connection to the network, physical network management, change of operator, full billing process support, payment, and debt management, customer communication, and finishing on customer account termination and network disconnection. The key market advantage of KMD Elements is its ability to support highly flexible, complex billing models as well as scalability to support large volumes of data. Our solution enables energy companies to promote efficient energy generation and usage patterns, supporting sustainable and green energy generation and consumption. We work with always up-to-date versions of: • Apache Spark on Azure Databricks • Apache Kafka • Delta Lake • Java • MS SQL Server and NoSQL storages like Elastic Search, Redis, Azure Data Explorer • Docker containers • Azure DevOps and fully automated CI/CD pipelines with Databricks Asset Bundles, ArgoCD, GitOps, Helm charts • Automated tests How do we work? #Agile #Scrum #Teamwork #CleanCode #CodeReview #Feedback #BestPracticies • We follow Scrum principles in our work – we work in biweekly iterations and produce production-ready functionalities at the end of each iteration – every 3 iterations we plan the next product release • We have end-to-end responsibility for the features we develop – from business requirements, through design and implementation up to running features on production • More than 75% of our work is spent on new product features • Our teams are cross-functional (7-8 persons) – they develop, test and maintain features they have built • Teams’ own domains in the solution and the corresponding system components • We value feedback and continuously seek improvements • We value software best practices and craftsmanship Product principles: • Domain model created using domain-driven design principles • Distributed event-driven architecture / microservices • Large-scale system for large volumes of data (>100TB data), processed by Apache Spark streaming and batch jobs powered by Databricks platform Your responsibilities: • Develop and maintain the leading IT solution for the energy market using Apache Spark, Databricks, Delta Lake, and Apache Kafka • Have end-to-end responsibility for the full lifecycle of features you develop • Design technical solutions for business requirements from the product roadmap • Maintain alignment with architectural principles defined on the project and organizational level • Ensure optimal performance through continuous monitoring and code optimization. • Refactor existing code and enhance system architecture to improve maintainability and scalability. • Design and evolve the test automation strategy, including technology stack and solution architecture. • Prepare reviews, participate in retrospectives, estimate user stories, and refine features ensuring their readiness for development. Personal requirements: • Have 4+ years of Apache Spark experience and have faced various data engineering challenges in batch or streaming • Have an interest in stream processing with Apache Spark Structured Streaming on top of Apache Kafka • Have experience leading technical solution designs • Have experience with distributed systems on a cloud platform • Have experience with large-scale systems in a microservice architecture • Are familiar with Git and CI/CD practice s and can design or implement the deployment process for your data pipelines • Possess a proactive approach and can-do attitude • Are excellent in English and Polish, both written and spoken • Have a higher education in computer science or a related field • Are a team player with strong communication skills Nice to have requirements: • Apache Spark Structured Streaming • Azure • Domain Driven Development • Docker containers and Kubernetes • Message brokers (i.e. Kafka) and event-driven architecture • Agile/Scrum Our offer: • Contract type: B2B • Work Mode : Flexible — this role supports on-site , hybrid , and remote arrangements, depending on your individual preferences. • Occasional on-site presence may be required — for example, onboard new team members, explore new business domains, or refine requirements in close collaboration with stakeholders or team building activities. What does the recruitment process look like? • Phone conversation with Recruitment Partner • Technical interview with the Hiring Team • Cognitive test • Offer

🏢 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 .