Analytics Engineer – Build Feature Stores & Data Pipelines

About the role

We are looking for an Analytics Engineer to design, develop, and monitor data products, especially feature stores, that enable our Data Scientists to deliver robust machine‑learning solutions. You will bridge the gap between data engineering and data science, ensuring high‑quality data pipelines and seamless model deployment.

Key responsibilities

• Collaborate with Data Scientists to design datasets for statistical and ML models.
• Design, develop, and maintain feature stores and associated feature pipelines for training and batch inference.
• Implement data quality and integrity checks to meet SLA requirements.
• Coordinate with Data Engineering and Data Governance teams to advance data maturity.
• Provide and maintain software packages that streamline model development workflows.
• Build CI/CD pipelines to accelerate deployment and catch issues early.
• Guide best practices for code and architecture, conducting reviews as needed.
• Communicate technical solutions and document architecture and systems.

Required profile

• Bachelor’s degree in a quantitative discipline (e.g., Computer Science, Math, Physics).
• Minimum 3 years experience translating business logic into data models.
• At least 3 years experience creating, building, and maintaining ETL pipelines.
• At least 1 year experience managing stakeholder relationships.

Required skills

• Feature store development and management.
• ETL pipeline design and implementation.
• CI/CD pipeline construction and automation.
• Data quality and integrity validation.

What we offer

• Opportunity to work on cutting‑edge data products.
• Collaborative environment with Data Scientists and Engineers.
• Professional growth in a fast‑moving analytics team.