About the Opportunity:

You will join a high-impact team that maintains and evolves the data platform powering our AI pipelines. This is an all-rounder role that combines backend development, data engineering, infrastructure, and lightweight frontend work.

Your work will span the ingestion layer, transformation workflows, and the warehouse itself: designing resilient pipelines, building secure APIs, and creating services that make our datasets reliable, discoverable, and ready for large-scale training. You will also play a key role in rearchitecting existing systems into generic, reusable components, moving away from point solutions toward a data collection platform that can serve multiple programs without being rebuilt each time.

You will be a key contributor to the infrastructure that feeds and monitors our machine learning models in production: ensuring that data flows seamlessly, services run reliably, and governance standards are never compromised. Every solution you build will follow the highest security standards and rigorous data governance principles, ensuring sensitive biometric data is handled with absolute care.

This role is onsite 5 days/week and sits in our Munich office.

Key Responsibilities:

Design and operate automated data quality pipelines with human-in-the-loop review stages, combining automated checks with structured labeling workflows to determine whether ingested data meets acceptance criteria
Develop and refine transformation processes to deliver clean, well-structured datasets ready for analytics, model training, and evaluation: production-grade, with strong schema contracts
Instrument systems with metrics, alerts, and recovery mechanisms, and build internal tooling and dashboards that make dataset health, pipeline state, and operational metrics visible to engineers and stakeholders
Build APIs and backend services that provide secure, performant access to large datasets while upholding strict governance and privacy controls
Raise engineering standards by improving CI/CD pipelines, integration tests, and dependency management
Own the lifecycle of critical data assets, including lineage tracking, access control, and schema enforcement

You will work with both structured and semi-structured data, combining SQL-based platforms like Snowflake with NoSQL sources like MongoDB. You'll build resilient pipelines that handle versioning, schema evolution, and are GDPR compliant.

About You:

5+ years of proficiency in Python, with experience building production services
Strong system design fundamentals, with experience evolving existing systems toward more generic, reusable designs
Experience designing and building APIs with security and performance requirements
Comfortable with containerization and orchestration tools like Docker and Kubernetes
Experienced with AWS services (S3, KMS, IAM) and Terraform for infrastructure as code
Skilled in designing and operating data ingestion and transformation workflows, with exposure to Snowflake or other SQL-based analytics platforms
Familiar with CI/CD pipelines and version control practices, ideally using GitHub Actions or similar tools
Committed to building systems that are secure, observable, and follow strong data governance principles
Obsessed with reliability, observability, and data governance, you care deeply about logs, metrics, and traceability
Experience with structured logging, metrics instrumentation, and alerting
Strong fundamentals in data modeling, schema design, and backward-compatible schema evolution
Comfortable working with NoSQL systems like MongoDB, especially for building ingestion frameworks, managing schema evolution, or integrating Change Streams into ETL pipelines
Knowledge of data partitioning strategies and large-scale dataset optimization for analytics and ML
Experience with event-driven data pipelines using SQS, SNS, Lambda, or Step Functions

Nice to have:

Proficiency in Go
Familiarity with annotation or labeling workflows and tooling
Exposure to monitoring and alerting stacks such as Datadog or Prometheus
Proficiency in Rust or an interest in learning it

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