Data Engineer

Build the data and AI foundation behind real trading and risk decisions, on a genuinely modern data stack. Who we are Lind Capital is a proprietary trading company focused on the financial markets. We combine market expertise, cutting-edge technology, data-driven decisions, and quantitative models to execute the best possible trades. We bring together talented people from diverse backgrounds in an informal work environment focused on creating results together. We empower our team to make decisions and prefer direct collaboration over bureaucracy. Our diverse team of 25+ are based in Aarhus, Denmark. The role Data and AI are central to Lind Capital’s success and key to our future growth, and we are looking to add to our data team that currently consists of six Data and ML Engineers. We run a modern data stack centered on Python (incl. Polars), Airflow, Parquet and Apache Iceberg, with Athena, Postgres, Kafka, and more in the mix. In this role, you’ll turn structured and unstructured data into trusted, well-modeled datasets that power production applications, analytics, and reporting — while helping us expand reliability, performance, and capabilities across our Data Lakehouse. You won't just feed data to AI applications — you'll help build them. You'll work in a team that actively experiments with AI across both agentic engineering and agentic workflows — from AI-assisted development to the internal AI tooling we develop ourselves. Key responsibilities

• Collaborate closely with trading and risk professionals to define data needs and translate them into durable datasets and interfaces.
• Design, build, and operate batch and streaming pipelines in our cloud-based Data Lakehouse.
• Use AI-assisted development tools fluently and help build the data foundations and internal tooling that let AI and ML systems work reliably and safely against our data.
• Implement data quality checks and improve pipeline observability (monitoring, alerting, and fast debugging when things break).

What we offer

• A genuinely modern data stack where the data products and AI tools you build visibly drive live investment and risk decisions — real impact, at a firm small enough that it shows.
• Close mentorship from six experienced Data and ML Engineers, with the support and code reviews to help you level up quickly.
• A culture grounded in quantitative thinking, curiosity, and experimentation.
• A dynamic environment that balances a disciplined approach to data pipelines with the freedom to innovate.
• An inclusive, caring, and psychologically safe workplace where diverse perspectives, ideas, and approaches lead to high performance.

What we are looking for

• Some hands-on experience with Data or Software Engineering — through work, internships, or your own projects. We care more about how you think than years on a CV.
• Strong Python engineering skills (e.g. clean code, tests, packaging).
• Solid SQL, and a working understanding of data stores for both transactional and analytical workloads.
• Comfort with Git and good engineering habits — testing, CI/CD, and code review.
• Genuine interest in working with AI tools day-to-day — both using them to ship faster and thinking critically about where they help and where they don’t.
• A strong communicator and team player who thrives in a cross-functional team.

We value potential over perfect match, and we encourage you to apply even if you don't meet all the above. We consider candidates across experience levels. Location We support flexible working arrangements; however, success in this role depends on close collaboration, which works best when colleagues are physically together. You should therefore expect to work most of the time from our Aarhus office. Our working language is English, and we welcome applications from non-Danish speakers. Benefits

• Professional development and clear career growth opportunities.
• Competitive compensation and employee shares.
• Good maternity/paternity terms.
• Modern office environment with a healthy canteen and snacks.
• Visa support (if needed).

The practical stuff Start date: As soon as possible. To apply, please submit your CV, grade transcript, cover letter, and other relevant documents via the link below. Applications will be processed on a rolling basis.