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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.
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.
The Senior Data Engineer will design, build, and maintain scalable data pipelines and platforms using Python, PySpark, and GCP technologies. This role involves collaborating with cross-functional teams to automate data processes and implement modern software engineering practices.
The Data Engineer will migrate and modernize ETL processes and Oracle data structures to Azure using Microsoft Fabric. The role involves building analytical models in PowerBI, optimizing performance, and maintaining data pipelines.
The Data Engineer will design and implement batch and streaming data pipelines, manage ETL/ELT processes, and ensure data quality. The role requires proficiency in Python, Java, or Scala, along with experience in Spark, SQL, and cloud platforms like AWS.
Designs and builds cloud-based data platforms (warehouses, lakes) using Azure tools, ensuring data quality, governance, and seamless ETL pipelines while collaborating with stakeholders to modernize legacy systems and support AI/ML use cases in sectors like retail, manufacturing, and finance.
This Senior Data Engineer role involves building data-quality frameworks and high-throughput pipelines for fraud detection and AML systems within a European fintech company. The position requires deep domain expertise in transaction monitoring and strong Python skills to support automated decision engines.
The Data Engineer will design, implement, and maintain scalable data pipelines and ETL processes within Azure and Databricks environments. The role involves collaborating with cross-functional teams to build big data solutions and ensure high-quality data standards.
The Junior Data Engineer will join the AI Markets team to develop and optimize kdb+ time-series databases, building analytic layers and APIs for traders and quants. The role involves working with large datasets, performance tuning, and integrating data with AI/ML workflows.
The Data Engineer will migrate and modernize ETL processes and Oracle data structures to Azure using Microsoft Fabric, while developing analytical models in PowerBI. The role requires advanced Python and SQL skills, experience with Azure cloud services, and the ability to work in a hybrid model in Warsaw.
Data Engineer designing and maintaining real-time data pipelines on GCP for a streaming platform, using Terraform, Kubernetes/GKE, and observability tools.
Build and orchestrate production-grade data pipelines and Data Lake/DWH solutions on Google Cloud Platform using Python, SQL, BigQuery, and Airflow in a hybrid role based in Kraków.
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