Senior Data Engineer - Data Foundation & Analytics (m/f/d)
Quick Summary
Define and implement core data models (users, events, performance) Design and operate robust,
5-7+ years of professional experience in data-heavy roles (data engineering, ML engineering, or similar). Strong programming skills in Python (clean architecture, testing,
Location: Hybrid/ Remote (Germany-based)
Start: ASAP | Languages: Fluent English
Note that we cannot provide any visa support.
Make the Unseen seen! Our goal is to reinvent scouting in football and build the #1 global scouting platform for identifying and developing talent. With the help of modern AI technology, CUJU enables every young football talent to be seen – regardless of origin, gender, or social background. We create fair opportunities and transparent pathways into professional sports. Our platform connects athletes, clubs, and organizations worldwide to rethink scouting – data-driven, objective, and mobile. Together, we are shaping the next generation of global talent scouting.
🌟 Your Mission: As CUJU’s first Senior Data Engineer, you will build the data foundation of the company.
Your mission is to transform fragmented data across multiple systems into a reliable, scalable, and usable data layer that enables:
• Clear business metrics (e.g. MAU, retention)
• Product decision-making
• Future player performance insights
You will play a critical role in shaping how data is structured, connected, and used across CUJU.
🚀What You’ll Work On:
- Define and implement core data models (users, events, performance)
- Design and operate robust, production-grade data pipelines
- Establish a single source of truth for key business and product metrics
- Structure data for business and product analysis (retention, funnels, activation)
- Build and deploy data services and jobs on AWS (e.g. S3, Lambda, ECS/EKS, Glue, Athena, Redshift, etc.).
- Make pragmatic decisions on how data is stored, processed, and accessed
- Evaluate and introduce tools (e.g. BigQuery, Snowflake, Databricks) where they add clear value
- Ensure the architecture scales with product, AI, and data growth without overengineering
- Optimize pipelines for scalability, cost efficiency, and performance.
- Write clean, maintainable, and well-structured Python code following software engineering best practices.
- Work closely with Product, Engineering, AI, and Business teams
Requirements
~1 min read🧠 What You Bring:
- 5-7+ years of professional experience in data-heavy roles (data engineering, ML engineering, or similar).
- Strong programming skills in Python (clean architecture, testing, modular design not just scripts).
- Solid SQL skills and experience designing analytical schemas.
- Hands-on experience building production data pipelines and services.
- Strong experience with AWS and cloud-native data architectures.
- Familiarity with infrastructure concepts (CI/CD, monitoring, logging, deployments)
- Comfortable working with imperfect, real-world data and evolving requirements.
- Experience working in fast-paced or early-stage environments
- You understand that data work is software engineering.
- Excellent communication skills in English, with the ability to effectively collaborate with cross-functional and international teams.
- Passionate about sports, performance analytics, and leveraging data to make a real-world impact.
What We Offer
~2 min readLocation & Eligibility
Listing Details
- Posted
- January 12, 2026
- First seen
- May 18, 2026
- Last seen
- May 22, 2026
Posting Health
- Days active
- 1
- Repost count
- 0
- Trust Level
- 23%
- Scored at
- May 20, 2026
Signal breakdown
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