Analytics Engineer
RECUP
full-time
Posted on:
Location Type: Remote
Location: Germany
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About the role
- You develop and maintain our data infrastructure and ensure that our data pipelines run reliably, with high performance, and at scale.
- You build robust data models and continuously maintain them so they serve as the foundation for our KPI logic, reporting, and data-driven decisions.
- You are responsible for ensuring data quality — through automated data-quality checks, tests, and validated processes you ensure a single source of truth.
- In close collaboration with Finance and business teams you build dashboards and reports that deliver real value and create transparency.
- As a role model for data-driven decision-making you set standards, inspire colleagues, and help RECUP make better and more effective decisions.
- You continuously advance our self-service analytics landscape and enable teams to independently access a scalable, reliable, and modern data foundation.
Requirements
- Minimum 3 years of experience in Data Engineering or Analytics Engineering
- Solid experience with data-warehousing and decision-support frameworks (e.g., Airbyte, Power BI, Looker, Tableau)
- Strong knowledge of the Google ecosystem, e.g., GCP (BigQuery, Cloud Functions), Google Analytics, Optimize, or Google Tag Manager
- Confident SQL and Python skills to implement data models, pipelines, and automations efficiently
- Structured and self-directed working style with a high standard of quality
- Professional and confident presence combined with the ability to communicate complex topics clearly
- Entrepreneurial mindset: you understand business contexts, act in a data- and numbers-driven way, optimize processes, and automate where appropriate
- Affinity for AI tools and modern technologies and a willingness to integrate them into daily work
- Excellent German and English skills, both written and spoken
Benefits
- A responsible and meaningful role with real societal impact.
- A fast-growing, dynamic company that offers significant room for development and influence as well as flexible working models.
- Plenty of space for autonomous work and personal initiative.
- A personal, positive, and professional working environment and an open feedback culture that allows everyone to make mistakes — because that’s part of the process.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Data EngineeringAnalytics EngineeringSQLPythonData WarehousingDecision-Support FrameworksData ModelsData PipelinesAutomationsData Quality
Soft Skills
Structured Working StyleSelf-DirectedHigh Standard of QualityProfessional PresenceClear CommunicationEntrepreneurial MindsetProcess OptimizationAutomationCollaborationInspiration