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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.
The Data Engineer will support reporting environments and manage large datasets by translating business needs into technical solutions within a banking context.
The Senior Data Engineer will design scalable data models and build robust ETL pipelines using Databricks and Azure Data Factory. The role involves ensuring data quality and security while collaborating in an international Scrum environment.
ETL/Data Engineer building and optimizing data pipelines with Oracle, SQL/PL/SQL, Python, and Airflow (DAGs), deployed via CI/CD on OpenShift for PKO BP bank.
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…
General info: Rate: 190 PLN net + vat/ hour Type of contract: B2B, long term cooperation Model of work: hybrid, 1 day per week work from office (Gdańsk/ Warsaw/ Łódź) Introduction & Summary We are seeking a skilled…
Data Engineer maintaining and evolving a Microsoft Fabric platform, building medallion-architecture (bronze/silver/gold) data pipelines using Python/PySpark and Spark SQL.
Builds and migrates large-scale financial data pipelines using Python and PySpark on Azure, designing cloud-native architectures for a global fintech infrastructure provider.
Data engineer designing and building cloud-based analytics platforms and pipelines for Procter & Gamble's retail execution, working with Python, Apache Spark, Databricks, and Azure in a hybrid model.
Builds and maintains data pipelines in Microsoft Fabric and Azure for a fintech client, transforming raw data into clean, auditable datasets using PySpark and SQL.
Design and implement data pipelines in Microsoft Fabric using Data Factory and PySpark notebooks for an insurance-industry project, working hybrid from Warsaw on a B2B basis.
Data Engineer designing and implementing data pipelines, PySpark notebooks, and data quality rules on Microsoft Fabric for an insurance-sector project, working hybrid from Warsaw.
Design and build scalable data pipelines on Azure Databricks and related Azure services to support analytics and reporting.
Design, build, and optimize scalable Snowflake data pipelines and multi-cloud solutions (AWS, Azure, GCP) for a pharmaceutical client, using DBT, Python, Tableau, and Terraform.
Build and optimize KDB+/q time-series databases for financial markets, creating low-latency analytics and APIs used by traders, quants, and AI models.
Senior Data Engineer on a 100% remote AML project for a financial-sector client, building and migrating ETL pipelines and data architectures using Python, SQL (Teradata), and PySpark/Databricks.
Data Engineer responsible for designing, developing, and maintaining high-performance data pipelines on Google Cloud Platform, working with real-time data processing, event-driven architecture, and infrastructure as code using Terraform and Kubernetes.
Senior Azure Data Engineer to architect a medallion lakehouse for a multitenant SaaS platform, guiding stack decisions and using AI/LLM tools for implementation rather than hands-on coding.
Senior Data Engineer builds and optimizes Google Cloud data pipelines, focusing on BigQuery, SQL, and Python to support financial-sector data transformation.
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