Senior Data Solutions Engineer (SQL and Python) for banking

Open 17d

Industry: banking

Location: hybrid - 3 days per week from office in Warsaw or Gdańsk

Rate: 165 pln/h on b2b

Summary: The primary objective of this role is to design and maintain data models that support credit and financial data processes. This position focuses on translating business requirements into scalable technical solutions, ensuring data quality, and facilitating collaboration between technical and non-technical teams.

Main Responsibilities:

  • Design and maintain data models supporting credit and financial data processes.

  • Analyse business requirements and translate them into scalable technical solutions.

  • Define and manage data mappings between multiple systems to ensure accurate data integration and transformation.

  • Ensure data quality, consistency, traceability, and auditability across the solution landscape.

  • Collaborate with business stakeholders, architects, and development teams on end-to-end solution design.

  • Prepare and maintain technical documentation and functional specifications.

  • Support process optimization and automation using AI-assisted tools.

  • Participate in solution implementation, testing, and continuous improvement activities.

Key Requirements:

  • Extensive experience in data modeling and solution design.

  • Strong SQL skills and hands-on experience with relational databases.

  • Good programming skills in Python.

  • Experience with data integration, transformation, and data mapping across multiple systems.

  • Understanding of APIs, system integrations, and process modeling.

  • Experience ensuring data quality, consistency, and governance standards.

  • Strong analytical and problem-solving skills.

  • Experience working directly with business stakeholders and translating business requirements into technical solutions.

  • Fluent English, both written and spoken.

Nice to Have:

  • Knowledge of Kafka.

  • Experience with Power BI.

  • Familiarity with Java development.

  • Understanding of data warehouse concepts and architecture.

  • Experience using AI tools for documentation, testing, data analysis or development support.

  • Experience in banking, finance, or regulatory reporting environments.

  • Knowledge of credit risk, rating, or financial statement data domains.