Data Engineer

Key Responsibilities:

• Collaborate with Business Analysts and Product Owners to clarify requirements and align priorities
• Design, build, and maintain SQL procedures and datasets reflecting business logic
• Develop and automate data pipelines using Apache Airflow
• Write clean, standardized Python and SQL code following best practices
• Identify and resolve data quality or performance issues

Must-Have Requirements:

• 4+ years of hands-on experience in Data Engineering
• Strong knowledge of SQL (4+ years), Python, and Git
• Proven experience with Apache Airflow for pipeline automation
• Understanding of SDLC principles and version control
• Excellent communication and collaboration skills in English

Nice to Have:

• Experience with Sybase or other enterprise databases
• Background in banking or financial data environments

We offer:

• Full remote
• B2B contract
• Salary is 4500-5500 EUR GROSS/month

Recruitment Process:

• CV Screening: Applications are reviewed within 24 hours.
• Pre-Screening Interview: A brief Q/A session (Automated or with a Recruiter) designed to learn more about your experience related to the required job position.
  1. Automated Session (Recommended) – You can complete this session on your own at a time that is convenient for you. The questions and follow-ups are well-structured and designed to highlight your experience and provide detailed insights into your background. This option is recommended because it's usually more detailed and allows us to provide feedback from the hiring manager faster.
  2. Session with a Recruiter – You can also have the session with a recruiter. The questions are the same, but the discussion may be a bit less detailed, and feedback might take a little longer.

• Shortlisting: Qualified candidates are presented to the hiring manager for review.
• Formal Interviews: On-site discussions with the hiring manager or project team, with feedback provided within 1-2 weeks.
• Offer and Onboarding: Successful candidates receive a formal offer and begin a structured onboarding process.

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