Senior Data Engineer (AWS)

Softeta is a software engineering partner for finance, energy, industrial, and other high-stakes sectors. We specialize in building and modernizing backend-heavy, integration-critical systems where speed, accuracy, and reliability are non-negotiable. With 90+ AI and custom software experts across engineering hubs in Lithuania and Poland, we embed ourselves directly into client operations — delivering custom software, automation, and AI where they drive the most value.

We are seeking for a Senior Data Engineer for our client from the banking sector.

Job description:

• Design, develop, and own end‑to‑end data pipelines, ETL/ELT processes, and large‑scale data products.
• Lead the design, implementation, and evolution of Data Lakehouse architectures using AWS services and open table formats.
• Build and operate large‑scale data processing solutions using Apache Spark on AWS EMR.
• Develop and orchestrate workflows using Apache Airflow.
• Integrate data from multiple internal and external sources, ensuring high data quality, performance, and reliability.
• Enable analytical access through Amazon Athena and support downstream reporting in PowerBI.
• Identify scalability, performance, and data quality issues and drive continuous improvements.
• Collaborate with existing Oracle or Sybase data warehouses during transition or coexistence phases when needed.

• Strong experience in data engineering within enterprise environments.
• Advanced SQL skills and solid understanding of analytical and dimensional data modeling.
• Hands‑on experience with Data Lakehouse or modern data platform concepts (cloud object storage, open table formats, distributed processing).
• Proven experience with AWS data services.
• Strong experience with Apache Spark for large‑scale data processing.
• Solid Python skills for ETL development, data processing, and automation.
• Experience designing, implementing, and maintaining robust and reliable data pipelines.
• Fluent English.

• Diverse and technically challenging projects.
• Flexible working hours and a hybrid or remote workplace model.
• Flexible schedule and an Agile/SCRUM environment.
• Technical equipment that you can choose.