Senior Data Platform Engineer - ML Pipelines & Lakehouse

Straumann Group; Województwo pomorskie; On-site; PLN 180,000 - 280,000; Full time

Job summary

Straumann Group is seeking a Senior Data Platform / Data Engineer to join our ML Platform team. You will help build and scale data infrastructure powering AI products in dentistry, spanning raw data ingestion to model training pipelines.

You will work with ML Researchers, MLOps, and product teams to ensure reliable, scalable data systems. Responsibilities include owning the data platform, managing dataset lifecycle with DVC, and implementing pipelines and data governance across AWS-based

Qualifications

• Strong Python engineering skills.
• Experience building data pipelines or data platforms.
• Experience working with AWS.
• Experience working with large datasets used in ML workflows.
• Strong software engineering practices (testing, CI/CD, documentation).
• Experience collaborating with ML teams or working in AI environments.

Responsibilities

• Data platform ownership: design and evolve the Data Lakehouse architecture used across ML teams.
• Dataset lifecycle management: versioning and reproducibility using DVC; manage multiple dataset versions across experiments.
• Data pipelines and infrastructure: build and maintain scalable Python-based data pipelines; improve metadata and data quality monitoring.
• Collaboration with ML teams: support researchers with reliable data access patterns and translate requirements into platform capabilities.
• Data governance and quality: enforce reproducibility and traceability across the ML lifecycle; ensure compliance for regulated AI development.

Skills

Python

Data pipelines

AWS

ML datasets

CI/CD

ML collaboration

Tools

DVC

Kubernetes

PostgreSQL

Metabase

Job description

Straumann Group is seeking a Senior Data Platform / Data Engineer to join our ML Platform team. You will help build and scale data infrastructure powering AI products in dentistry, spanning raw data ingestion to model training pipelines.

You will work with ML Researchers, MLOps, and product teams to ensure reliable, scalable data systems. Responsibilities include owning the data platform, managing dataset lifecycle with DVC, and implementing pipelines and data governance across AWS-based