Senior Data Engineer (Snowflake)
⚲ Gdańsk, Gdynia, Warszawa
23 520 - 30 240 PLN netto (B2B)
Wymagania
- Big Data
- Databases
- Snowflake
- DBT
- Airflow
- DB2
- CI/CD
- Data Warehousing
Opis stanowiska
Senior Data Engineer (Snowflake)
•
Location: Hybrid (4 days in the office, 1 day remote) – Warsaw or Gdańsk
• Salary: up to 180 PLN / hour (B2B)
• Company: A prominent player in the banking industry.
About the Role:
You will be joining the Corporate Credit unit, specifically within the Limit Management technology team. This team builds and maintains the core digital solutions that drive corporate credit decisions across the bank, ensuring real-time limit checks, regulatory compliance, and risk monitoring. We are looking for a highly skilled and proactive Senior Data Engineer to support the foundational phase of a new data engineering team and build scalable data solutions from scratch.
Key Responsibilities:
• Take full, end-to-end ownership of designing and building robust data models and data pipelines.
• Drive the modernization process, transitioning from fragmented local systems to a unified, modern data solution.
• Act as a bridge between business stakeholders and the engineering team, proactively translating complex business problems into actionable data solutions.
• Drive quality and technical leadership by setting high delivery standards 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 speed and productivity.
Requirements:
• Strong, proven experience in data engineering and building large-scale modern data warehousing solutions.
• Hands-on, advanced experience with Snowflake, dbt, and Airflow.
• Solid experience with CI/CD, pipeline orchestration, and modern data engineering practices.
• A strategic mindset: you prioritize long-term maintainability over short-term fixes and understand what "good" looks like in data architecture.
• A "natural investigator" approach—you don't wait for detailed specifications but proactively explore the business domain to clarify requirements.
• Fluent English (Advanced/C1) for seamless communication with international stakeholders.
• Nice to have: Experience with DB2.
What We Offer:
• Salary: up to 180 PLN net + VAT per hour.
• Contract: B2B.
• Work Model: Hybrid (4 days from the office, 1 day from home) located in either Warsaw or Gdańsk.
• Impact: The opportunity to act as a foundational member of a newly formed team, shaping the data architecture and processes from the ground up.
• Innovation: A dynamic environment where you are encouraged to use the newest AI tools to enhance your daily work.
•
Location: Hybrid (4 days in the office, 1 day remote) – Warsaw or Gdańsk
• Salary: up to 180 PLN / hour (B2B)
• Company: A prominent player in the banking industry.
About the Role:
You will be joining the Corporate Credit unit, specifically within the Limit Management technology team. This team builds and maintains the core digital solutions that drive corporate credit decisions across the bank, ensuring real-time limit checks, regulatory compliance, and risk monitoring. We are looking for a highly skilled and proactive Senior Data Engineer to support the foundational phase of a new data engineering team and build scalable data solutions from scratch.
Key Responsibilities:
• Take full, end-to-end ownership of designing and building robust data models and data pipelines.
• Drive the modernization process, transitioning from fragmented local systems to a unified, modern data solution.
• Act as a bridge between business stakeholders and the engineering team, proactively translating complex business problems into actionable data solutions.
• Drive quality and technical leadership by setting high delivery standards 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 speed and productivity.
Requirements:
• Strong, proven experience in data engineering and building large-scale modern data warehousing solutions.
• Hands-on, advanced experience with Snowflake, dbt, and Airflow.
• Solid experience with CI/CD, pipeline orchestration, and modern data engineering practices.
• A strategic mindset: you prioritize long-term maintainability over short-term fixes and understand what "good" looks like in data architecture.
• A "natural investigator" approach—you don't wait for detailed specifications but proactively explore the business domain to clarify requirements.
• Fluent English (Advanced/C1) for seamless communication with international stakeholders.
• Nice to have: Experience with DB2.
What We Offer:
• Salary: up to 180 PLN net + VAT per hour.
• Contract: B2B.
• Work Model: Hybrid (4 days from the office, 1 day from home) located in either Warsaw or Gdańsk.
• Impact: The opportunity to act as a foundational member of a newly formed team, shaping the data architecture and processes from the ground up.
• Innovation: A dynamic environment where you are encouraged to use the newest AI tools to enhance your daily work.
🔍 Dekoder Ogłoszenia
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Take full, end-to-end ownership of designing and building robust data models and data pipelines.
Oznacza to, że będziesz odpowiedzialny za cały proces od koncepcji po wdrożenie, co może wiązać się z dużą ilością pracy i samodzielności.
🔴
Act as a bridge between business stakeholders and the engineering team, proactively translating complex business problems into actionable data solutions.
Może oznaczać, że będziesz musiał spędzać dużo czasu na spotkaniach z biznesem i wyjaśnianiu kwestii technicznych, co może odciągać od czystej inżynierii danych.
🔴
Drive the modernization process, transitioning from fragmented local systems to a unified, modern data solution.
Sugestia, że obecne systemy są przestarzałe i mogą wymagać znaczących nakładów pracy na ich refaktoryzację lub całkowitą przebudowę.
🔴
Pioneer AI adoption by implementing AI-assisted development practices (e.g., GitHub Copilot, internal agents) to improve engineering speed and productivity.
Może oznaczać, że firma jest na wczesnym etapie wdrażania AI i będziesz musiał nie tylko używać tych narzędzi, ale także pomagać w ich konfiguracji i integracji.
🔴
foundational phase of a new data engineering team and build scalable data solutions from scratch.
Oznacza, że będziesz częścią zespołu tworzonego od podstaw, co wiąże się z budowaniem procesów i narzędzi od zera, a nie tylko pracą nad istniejącymi rozwiązaniami.