Data Engineer: ML Pipelines & Production-Ready Data

Cari; København; Hybrid; DKK 687.000 - 945.000; Vollzeit

Zusammenfassung

Lundbeck seeks a Data Engineer to build the data foundation for strategic AI use cases and own the MLOps infrastructure to productionize models. You'll join GCX's data, insights and AI team and initially focus on ingesting data from multiple commercial sources, standardizing definitions and delivering a shared data model.

As models mature, your scope expands to CI/CD for deployment, model monitoring, and scalable infrastructure using Docker, Kubernetes, and Terraform across Azure and/or AWS.

Qualifikationen

• Several years of experience building data pipelines and integrating data across complex enterprise systems.
• Strong Python and SQL, with solid engineering practices (Git, testing, documentation, reusable code).
• Experience with cloud platforms and infrastructure as code.
• Experience with Docker and Kubernetes.
• Understanding of data modeling, taxonomy design and data quality practices for messy, fragmented or newly created data sources.
• Comfort working in ambiguity, building foundational infrastructure before the full picture of downstream use cases is settled.
• Strong communication skills and the ability to partner closely with data scientists, engineers and BI colleagues.

Aufgaben

• Data engineering: building and maintaining data pipelines that ingest and integrate data from enterprise systems.
• Designing a shared taxonomy and data model across fragmented sources for a common foundation.
• Ensuring data quality, consistency and reliability for analytics, ML and GenAI use cases.
• Partnering with Data Scientists and GenAI Engineer to unblock work with clean, well-structured data.
• Partnering with BI to ensure reporting and predictive pipelines draw from the same reliable foundation.
• Building CI/CD pipelines for model deployment and implementing experiment tracking and model registries (e.g. MLflow).
• Setting up model monitoring for performance, drift and reliability in production.
• Supporting containerization and deployment via Docker and Kubernetes or cloud platforms.
• Establishing best practices for moving models from prototype to production across the team.
• Managing cloud infrastructure (Azure and/or AWS) supporting data and ML workloads.
• Applying infrastructure as code (Terraform) for reproducible environments.
• Implementing security, access control and secure coding practices across data and ML stack.
• Automating operational tasks and maintaining Linux-based environments.

Kenntnisse

Python

SQL

Git

Testing

Documentation

Communication

Ausbildung

Degree in computer science or related field

Tools

Docker

Kubernetes

Terraform

Jobbeschreibung

Lundbeck seeks a Data Engineer to build the data foundation for strategic AI use cases and own the MLOps infrastructure to productionize models. You'll join GCX's data, insights and AI team and initially focus on ingesting data from multiple commercial sources, standardizing definitions and delivering a shared data model.

As models mature, your scope expands to CI/CD for deployment, model monitoring, and scalable infrastructure using Docker, Kubernetes, and Terraform across Azure and/or AWS.