Data Engineer (m/f/d) at Flix SE
10115 Berlin, , Germany -
Full Time


Start Date

Immediate

Expiry Date

11 Nov, 25

Salary

0.0

Posted On

12 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

OUR PERKS – MORE THAN JUST A JOB:

  • Travel perks: 12 free Flix vouchers + 12 discount vouchers for friends & family.
  • Work from (M)Anywhere: Depending on your role, work from another location for up to 60 days per year.
  • Hybrid work model: We are an office-first company, but we offer flexibility to balance work and life.
  • Wellbeing support: Access confidential 1:1 counselling, courses, and stress management for yourself and up to four family members.
  • Learning & Development: Take advantage of language classes, training courses, and expert-led sessions to grow your skills.
  • Mentoring Program: Connect with experienced colleagues to gain insights and accelerate your career.

How To Apply:

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Responsibilities
  • Use Python, SQL, and Airflow to design and maintain robust, scalable data pipelines that deliver timely, actionable insights to marketing stakeholders.
  • Apply analytical thinking to understand complex data requirements and translate them into efficient data pipelines.
  • Ensure data quality through validation, monitoring, and clear documentation.
  • Proactively debug and refactor data pipelines to enhance performance, accuracy, and maintainability, based on a solid understanding of the underlying business logic.
  • Participate in code reviews and contribute to engineering best practices within the team.
  • Collaborate with the Product Owner and cross-functional teams to understand marketing stakeholders’ data needs and translate them into technical solutions.
  • Assist with ad hoc requests and help resolve data-related issues by applying both technical and analytical problem-solving skills.
  • Participate in the continuous improvement of data infrastructure by optimizing pipeline performance, enhancing data models, and integrating scalable, future-proof solutions.
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