Senior Data Engineer
Summary
Senior Data Engineer for a 12-month B2B contract on a banking client project, building end-to-end data solutions across AWS cloud and on-prem Oracle DB. Day-to-day work centers on ETL/ELT pipelines with Airflow, dbt, and SAP Data Services, plus Data Mesh and Medallion architecture implementations.
Role Overview:
We are looking for an experienced Senior Data Engineer to join a cross-functional Agile team within the banking domain. The role focuses on designing and improving end-to-end data solutions across AWS cloud and on-premises (Oracle DB) environments, working with Airflow, dbt, and SAP Data Services, and contributing to Data Mesh and Medallion architecture implementations.
Project/Client: Banking
Location: Baltic States and Poland Citizen (remote)
Start Date: ASAP
Duration: 12 months
Language: English
Hourly rate: 35 - 40 EUR. B2B contract.
Key Responsibilities:
- Design, implement, and improve data ingestion, processing, storage, and sharing within a Data Mesh platform across AWS cloud and legacy DWH environments
- Build and optimize ETL/ELT pipelines and data architectures using Airflow, dbt, and SAP Data Services
- Support modernization and migration of legacy data systems toward cloud-native architecture
- Ensure high standards of data quality, security, and performance across all data workflows
- Collaborate with analysts, engineers, and business stakeholders to deliver scalable data solutions
- Perform code reviews, implement monitoring and alerting, and resolve data pipeline defects
- Participate in the EOD ROTA rotation, with availability for incident resolution until 23:00-24:00
Must-Have Requirements:
- Proven hands-on experience with SQL and Python
- Hands-on experience with cloud platforms - AWS, Azure, or GCP
- Good understanding of data pipeline tools such as Airflow or dbt
- Working knowledge of enterprise data platforms: Oracle DB, SAP IQ, SAP Data Services, and SAP Business Objects
- Knowledge of solution integrations - real-time, message-based, and event-driven architectures - including bridging legacy systems with modern data platforms
- Exposure to test automation and DevOps practices, including infrastructure as code, security best practices, CI/CD, and SDLC
- Experience with Data Products deliveries, Medallion architecture, and Data Mesh architecture
- Strong communication and collaboration skills