Pracuj.pl Hybrydowo Senior New

Senior Data Engineer

B2B.NET S.A.

⚲ Gdańsk, Warszawa

120–135 zł netto (+ VAT) / godz.

Wymagania

  • Snowflake
  • dbt
  • Airflow
  • GitHub Copilot

Opis stanowiska

Nasze wymagania: Strong experience in data engineering and data warehousing, building large-scale data solutions Ability to design data warehouse solutions, with a focus on simplicity and maintainability Hands-on experience with Snowflake, dbt, Airflow Comfortable taking full ownership from requirements to production Eager to understand the business domain so that you can turn their problems into robust and maintainable data solutions Solid experience with CI/CD, pipeline orchestration, and modern data engineering practices O projekcie: Our systems help credit professionals efficiently assess financial data, manage credit limits, and evaluate risk. We focus on creating reliable and intuitive tools that simplify complex workflows and support high-quality decision making. We are responsible for delivering and maintaining core credit solutions within Limit Management to ensure real-time limit checks and regulatory-compliant limit exposure monitoring, orchestrate integrations from exposure data sources and to credit decision systems, and support limit data services for risk monitoring and reporting. Zakres obowiązków: Support the foundational phase of our new data engineering team, turning business problems into data solutions Take ownership of designing and building data models and data pipelines Drive modernization from requirements to production, transitioning from fragmented local systems to unified solution Build trusted partnerships with Business and stakeholders through effective communication, discussing technical concepts and ensuring alignment throughout development process Drive quality and technical leadership by setting high delivery standards, emphasizing long-term reliability and maintainability, and championing modern engineering practices (TDD, design patterns, clean architecture) Pioneer AI adoption by implementing AI-assisted development practices (e.g. GitHub Copilot, internal agents) to improve engineering productivity