Data Engineer

at  Trackunit

You being a curious and analytical person, with great data engineering competencies, and a desire to make an impact on the world. Trackunit has a position as Data Engineer to offer.
In this role, you will be a part of our Finance organisation while also joining our engaged and active data community. You’ll be working alongside a core group of talented colleagues who take chances and challenge the status quo. Together with your team, you will be instrumental in creating the foundation for Trackunit’s future finance data enablement.
With locations in the hearts of Copenhagen, Kolding, Aarhus, and Aalborg, we offer you a flexible setup with the possibility to work from one of our locations or remotely from anywhere in Denmark. As many of your colleagues will be located out of Aalborg, we expect you to be present in Aalborg on a regular basis.

WHO ARE YOU IDEALLY?

You might already be a skilled data engineer, or you might be an experienced software developer looking for a next step, but most importantly, you feel at home with Spark, Python, Kafka, and large amounts of data.

You will be most impactful as a Data Engineer at Trackunit if:

• You have experience with some or all of the Databricks platform (Spark, Delta Lake, MLflow), or similar technologies
• You have experience using Python for data processing, possibly in a financial context
• You have experience with AWS or similiar cloud providers
• You take pride in writing well-designed, tested code, and peer reviews are part of your way of working
• You see yourself as someone who understands how to enable others, and you thrive in a high paced global environment

Don’t meet every single requirement? No worries - this is what we’re looking for ideally, but if you’re super excited about this role but your past experience doesn’t align perfectly with every qualification, we encourage you to apply.

At Trackunit every day is different, but you can expect to:

• Build and operate data pipelines (python) with our financial data from our ERP system, including extracting and processing data.
• Understand use cases of the financial data across Trackunit, and ensure the data architecture supports these effectively.
• Organise and structure the way our financial data is stored for use across a variety of data sources and use cases.
• Setup jobs for scheduling and automisation of the data pipelines (Airflow).
• Work with financial experts and skilled data engineering colleagues to ensure a solid foundation for effective reporting across Trackunit.
• Engage with data scientists and other data consumers to understand how data will be used, and follow up by preparing and providing data.
• Work with some of the best data technologies currently available, e.g. Databricks, Python, Airflow, Kafka and Power BI.