We are looking for a Lead – Data Pipeline Engineering to lead a team while designing, building, and operating data pipelines that power live trading across various energy markets within our newly established power trading business.
You will sit at the intersection of data engineering, platform reliability, and trading operations, ensuring that time-critical data flows support smooth operations and analytical efforts.
If you enjoy combining technical leadership with team development and want to build a modern data platform for live trading, this role is for you.
About the Role
You will work daily within a dedicated power trading team in Aalborg and lead a small group of data engineers across a distributed setup. As the lead for this area, you will set direction, guide technical decisions, mentor the team, and ensure that the right capabilities and ways of working are in place.
This remains a very hands-on senior role: you will contribute directly to architecture, data pipelines, and production systems while also ensuring alignment, coordination, and continuous improvement across the team.
You will have the opportunity to shape the team’s future setup and drive changes that strengthen our data platform and its ability to support trading.
Architecture, Data Pipelines, and Reliability for Trading Systems
- Shape the vision for our data platform and bring that vision from idea to reality.
- Design and implement scalable data pipelines across batch and streaming use cases.
- Build and extend our cloud native data platform on Azure – focused on reliability, speed, and efficiency.
- Develop a team of data engineers, ensuring clear priorities, strong collaboration, and a high-quality engineering culture.
- Work on observability and monitoring of live trading systems and data pipelines to ensure stable operations
- Serve as a bridge between technical and business stakeholders – turning business needs into tradable data.
Qualifications
- 5+ years of relevant experience in data engineering, data platform engineering, or data architecture.
- Strong experience designing and operating production-grade data pipelines.
- Experience guiding technical work and mentoring colleagues.
- Excellent communication skills and ability to collaborate across teams and time zones.
- Comfortable working in an environment with evolving priorities and operational responsibility.
- Experience with power markets or trading systems (financial or energy markets) is a plus.
- Experience with cloud-based storage patterns for time series datasets (weather, load/generation, prices, balancing services, etc.).
- Exposure to ML/AI enablement (data readiness, feature pipelines, model monitoring) – not required but valued.
Core Technologies
You will be responsible for setting direction in key areas of the technical stack, with limited technical debt and freedom within the soft boundaries outlined below:
- Core language: Python, but deviating when applicable.
- Deployment within Azure & container orchestration with e.g. Kubernetes
- PostgreSQL/Delta Lake (or similar lakehouse tech) for both OLAP & OTLP
- GitHub Actions / Azure DevOps
- Own choice of technologies for orchestration/streaming/monitoring
- Infrastructure as Code: Terraform / Bicep (nice-to-have)
- IoT integration (nice-to-have): MQTT
You Are…
- Someone who naturally takes responsibility, sets technical direction, and enjoys mentoring and elevating others.
- Skilled at balancing long-term thinking with hands-on engineering.
- Passionate about building high-quality, well-designed data systems.
- Able to translate business needs into scalable, pragmatic solutions.
Why Join Us
- Shape a modern cloud data platform that directly supports real-time trading.
- Solve meaningful engineering challenges across streaming, time series data, and cloud architecture.
- Work with skilled colleagues in an international, collaborative environment.
- Grow your expertise and influence as our trading platform and data landscape expand.
- Enjoy a high-trust culture where you can take ownership and make strong technical decisions.