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You will design and operate robust, production-grade data pipelines while defining core data models for the platform. Additionally, you will collaborate with cross-functional teams to ensure data architecture scales effectively with product and AI growth.
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.
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
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
Digital-First Approach: Great talent knows no borders! You can work from wherever you are — we hire and collaborate with professionals worldwide.
Remote Work Model: Balance your professional and personal life with our flexible working conditions, empowering you to deliver your best from anywhere.
Exciting Projects: Dive into impactful projects across industries that challenge and spark creativity.
Boost Your Expertise: Grow your career with continuous learning, development opportunities, and hands-on experience.
Join the Best Team Ever: Collaborate with our diverse and cross-cultural team of passionate technologists and creative thinkers.
We strive to make our hiring process smooth and transparent to find the perfect match for both sides. Steps may differ depending on the role, but here’s what to expect:
Initial Interview: If your background fits the role, we’ll invite you for an interview with a Talent Acquisition Specialist.
Technical Interview: Depending on the position, you may complete a technical assessment or test task.
Client Interview.
Final Decision: After all steps, we’ll get back to you with the result and next steps.
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