Posted today · be early
Senior Data Engineer
Opinov8
WorldwideremotePosted today
Skill Required
Data-EngineerMachine-Learning-EngineerPython-DeveloperSenior-Data-EngineeringSenior-Lead-Data-EngineeringSenior-Data-Engineer-JobsSenior-Data-Engineer-PositionsData-Platform-EngineerData Engineersoftware engineeringdata engineeringComputer VisionEngineeringDatabricksR ProgramminganalyticalObservabilitySnowflakedesigningsimilar)analyticsBigQueryRedshiftbuildingetc.)TestNGPythondesignSparkCI/CDCloudDesign PatternsSQLAWSFulltime
Key highlights
- Required experience: 5-7+ years
- Remote work model available
- Global hiring approach
- Focus on sports-tech industry
Role 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.
Responsibilities
- 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
- 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
Benefits
- 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.
Additional details
- Hiring process steps: Initial Interview with Talent Acquisition Specialist, Technical Interview (may include assessment or task), Client Interview, and Final Decision.
- Originally posted on Himalayas