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Dropi is seeking a Data Engineer to design and maintain scalable data pipelines and warehousing solutions using AWS technologies. The role involves collaborating with cross-functional teams to ensure data integrity and performance within their e-commerce platform.
Lead a data engineering team at Sanofi, designing and operating scalable data pipelines and platforms using Spark, Kafka, Snowflake, and AWS to support analytics and AI/ML use cases in the commercial business.
This early-stage full-stack engineering role involves building and maintaining end-to-end features, including data pipelines, multi-tenant architecture, and AI-driven UI components using Python, TypeScript, and React.
Design and lead enterprise-scale SQL Server data warehouse solutions that power critical business decisions at a global bank.
Design and implement scalable data platforms using Databricks Lakehouse, lead ETL modernization from Informatica to Databricks, and architect batch and real-time pipelines on cloud platforms using Spark, PySpark, SQL, and Delta Lake.
Principal role designing and engineering enterprise-grade data platforms, integrating Agentic AI, and enforcing Architecture as Code with CI/CD for scalable, governed data products in fintech.
The Staff Data Engineer will design and manage enterprise data architecture and pipelines using Azure Databricks, Power BI, and containerized solutions. This role focuses on optimizing data infrastructure, governance, and self-service analytics within the bank's Investor and Treasury Services division.
The Data and DevOps Engineer will design, automate, and maintain data workflows and business intelligence solutions using tools like Apache Airflow, Spark, and SQL. The role involves translating business needs into technical specifications, creating visualizations, and managing database systems.
This role involves designing and developing AI-based agents and intelligent automation solutions for RBC Wealth Management using Python, SQL, and Snowflake. The developer will work in a highly technical environment, leveraging AI-assisted coding tools to build scalable data pipelines and automated testing frameworks.
Data scientist designing and implementing ML and analytical models to support fraud detection, tax process improvement, and recovery optimization at Belgium's Federal Public Service for Finance, using SAS, SQL, R, and Python.
The Senior Data Engineer will develop and maintain a central data and analytics platform for the public sector, focusing on BI, data warehousing, integration, and AI projects using OpenShift.
Data Engineer/BI & AI consultant for a long-term public-sector project, developing and optimizing data warehouse solutions, data integration pipelines, and ML/GenAI applications using Oracle, Python, and OpenShift.
Designs and builds a greenfield enterprise data warehouse on Google BigQuery, consolidating fragmented systems (ERP, CRM, e-commerce, EDI, etc.) into a governed, decision-ready foundation for MRCOOL’s HVAC business. Focuses on ELT pipelines, data governance, AI enablement, and executive reporting.
Design and maintain data solutions in Microsoft Fabric, building architectures with OneLake, Lakehouse, Data Warehouse and Data Factory, implementing Medallion architecture and star models using PySpark, T-SQL, and Delta Lake.
The Azure Data Engineer will design and implement data analytics and warehouse solutions using Azure Data Factory, Databricks, and Kafka. This role requires 8-10 years of experience and involves working in an Agile environment with a hybrid schedule in Poland.
The Cloud Data Engineer will design, build, and maintain scalable data platforms and ETL/ELT pipelines using cloud technologies like AWS or Azure. The role involves collaborating with data analysts and scientists to optimize data processing and support business analytical needs.
Builds and maintains end-to-end data pipelines (dbt, Python, Airflow) and Power BI dashboards, bridging engineering and analytics to deliver production-ready solutions.
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.
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.
Wymagania Praktyczna znajomość ekosystemu Microsoft Fabric (OneLake, Lakehouse, Data Warehouse, Data Factory). Bardzo dobra znajomość PySpark (Python) oraz T-SQL. Doświadczenie z architekturą Medallion oraz…
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