Senior Data Engineer

PROJECT OVERVIEW Our client is an established product company in the sports-tech industry, delivering a mobile application focused on skill assessment and talent evaluation.

The platform enables users to record short performance exercises via smartphone, which are then processed using AI-based computer vision to generate objective performance metrics and rankings. The solution connects end users with organizations seeking data-driven insights for talent identification.

IN THIS ROLE, YOU WILL 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 IF YOU ARE 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 environm