About the role
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.
What they look for
Requirements
The role requires 5-7+ years of professional experience in data-heavy roles and strong programming skills in Python. Candidates must also possess solid SQL skills and hands-on experience with AWS cloud-native data architectures.
Benefits
Full description
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 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
AS AN OPINOV8R, YOU WILL HAVE
- 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.
HOW’S THE HIRING PROCESS GOING
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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