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The Data Engineer will build data pipelines using Microsoft Fabric, Data Factory, and PySpark, while managing data onboarding, transformation, and validation. The role involves implementing CI/CD practices and collaborating with risk teams to ensure data compliance in a hybrid work environment.
Data Engineer working with kdb+ and large real-time datasets, focusing on data engineering, performance optimization, and API integration for financial markets reporting and analytics.
Builds and maintains end-to-end data pipelines (dbt, Python, Airflow) and Power BI dashboards, bridging engineering and analytics to deliver production-ready solutions.
Designs and builds scalable data platforms on Azure Fabric/Databricks, translating business needs into lakehouse architectures while collaborating with BI teams on reporting and ensuring governance/automation.
Data Engineer working with Google BigQuery, Dataform, and Python to support migration and modernization of data and analytics processes, with monthly on-site presence in Warsaw.
Building automated Python and SQL data solutions and migrating legacy SQL Server logic to a scalable Python stack within the Data Control and Financial Engineering team.
The Data Engineer will modernize data and analytics workflows on Google Cloud Platform using BigQuery, Dataform, and Python. The role involves collaborating with teams and requires monthly visits to the client's office in Warsaw.
Cloud Data Engineer at Sii designing and developing Data Lake/Data Platform solutions, building ETL/ELT pipelines, and collaborating with BI and Data Science teams using SQL, Python, Spark, and Azure/AWS.
Senior SAP Datasphere Data Engineer building data flows, CDS Views on S/4HANA, and leading BW→Datasphere migration for a pharmaceutical client in Warsaw.
Senior Data Engineer building and optimizing Snowflake/Snowpark/dbt data workflows and developing AI/GenAI solutions for a financial-sector client, on a hybrid basis in Poland.
Build and maintain cloud data pipelines, warehouses, and analytics solutions using Azure/GCP/AWS, SQL, PySpark, and BI tools for enterprise clients.
Data Engineer migrating and modernizing data and analytics processes using BigQuery, Dataform, SQL, and Python, with occasional on-site client work in Warsaw.
Mid/Senior Data Engineer at Xebia designing and maintaining scalable GCP/BigQuery data pipelines, building ETL/ELT frameworks, and supporting migration projects using Python, SQL, and orchestration tools like Airflow.
As a Senior Data Engineer, you will design, develop, and optimize ETL/ELT pipelines and data architectures for diverse international clients using Python, SQL, Snowflake, dbt, and orchestration tools like Airflow or Dagster. You will work within a remote-friendly, autonomous team environment focused on delivering high-quality data solutions across cloud platforms.
Senior Data Engineer on a Regulatory Reporting team within an investment bank, building scalable data pipelines and data-driven applications using SQL, Databricks, Python, Spark, and Azure.
Senior PostgreSQL Data Engineer working on a banking application's data warehouse and big data pipelines in a multi-cloud (AWS/GCP) environment, using PostgreSQL, Python, and log analysis.
The Expert Data Engineer will design, develop, and optimize ETL processes and data warehouse solutions using Microsoft SQL Server, SSIS, and Snowflake. The role involves collaborating with cross-functional teams to maintain high-performance data pipelines and database architectures.
Erste Bank Polska is seeking a Data Engineer to develop reporting environments and bridge the gap between business requirements and technical implementation. The role involves collaborating with IT teams to deliver data solutions in a hybrid work model.
This Senior Data Engineer role involves designing and implementing enterprise-scale data platforms and ETL/ELT pipelines on AWS for a global pharmaceutical client. The position focuses on building scalable data solutions, ensuring system performance, and collaborating with cross-functional teams to drive data strategy.
Build and maintain a marketing analytics platform by integrating data sources, ensuring quality, and automating pipelines using Azure Databricks, PySpark, and Power BI.
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