Data Engineer - Data Science focus →

Cph Ai Hub; København; Hybrid; DKK 600,000 - 900,000; Full time

Job summary

Trackunit is seeking a Data Engineer for its Data Products team to design and operate end-to-end data pipelines and datasets powering analytics and future ML products. This hands-on role offers ownership in a small team, with collaboration across data science and Data Foundation engineers.

You will work with SQL, Python, Databricks, Spark and Delta Lake to ensure data quality, reliability, and scalability. The role supports a remote-friendly, international collaboration culture across

Qualifications

• Experience designing, building, and operating production data pipelines.
• Strong SQL, Python and data modelling skills.
• Experience with cloud data platforms and data quality monitoring.

Responsibilities

• Design and operate production data pipelines for analytics and ML.
• Collaborate with data science and data foundation teams on data prep, feature engineering and model deployment.
• Build automated data validation, monitoring, and alerting.

Skills

SQL

Python

Data modelling

Databricks

Spark

Delta Lake

CI/CD

Data quality

Tools

Databricks

Spark

Delta Lake

Airflow

Job description

_At Trackunit, we collect data from machines and job sites across the globe, and we are building the products that make that data useful. As a Data Engineer in our Data Products team, you will design and operate the pipelines and datasets that sit behind our analytics and future machine learning products. You will work closely with data science and alongside experienced engineers in our Data Foundation team. It is hands‑on work with real ownership, in a small team where what you build actually ships.

What’s in it for you?

Take ownership in a small team. Shape the data engineering work in our Data Products team, with a direct influence on how we build reliable, reusable products for customers.

Build the data behind new insights. Develop pipelines and datasets that support benchmarking, analytics, and future machine learning products as we move from individual customer solutions to products serving many customers.

Work with varied, challenging data. Combine equipment and sensor data with external sources, including satellite and weather data, and make it ready for analysis and modelling.

Work closely with data science. Partner with our data scientist on customer needs, solution design, and data preparation, with opportunities to grow into feature engineering, model deployment, and MLOps.

Learn through collaboration. Work alongside experienced engineers in our Data Foundation team, supported by an international culture of knowledge sharing, feedback, and professional development.

Who are you ideally?

• You have experience designing, building, and operating production data pipelines, with strong SQL, Python, and data modelling skills.
• Databricks expertise is a significant advantage. You ideally bring strong hands‑on experience building and operating pipelines with Spark and Delta Lake, managing data quality, and preparing datasets for analytics and machine learning.
• You treat data quality as part of the product. You build automated validation, monitoring, and alerting, and can investigate problems from a customer‑facing result back to the source.
• You have worked with cloud data platforms and tools for orchestrating and transforming data, and can make practical choices about reliability, performance, and cost.
• You understand how to keep pipelines maintainable as data sources change, using testing, CI/CD, clear documentation, and thoughtful handling of schemas and dependencies.
• You have worked alongside data scientists, or bring a strong understanding of their needs, including preparing reliable datasets for exploration, feature engineering, and model training.
• You enjoy contributing to requirements and solution design, translating customer needs into practical data solutions, and taking ownership while collaborating across teams.
• Experience integrating external APIs and feeds, working with geospatial or time series data, or processing large datasets efficiently would be a plus. Interest in model deployment and MLOps is welcome. You don’t need to tick every box. If data engineering is your core strength and you’re curious about data science and the products it enables, we’d like to hear from you.

Our hiring process

Don't waste your time on writing the best possible cover letter for the job. We want you to create an impact that matters, and that's not in the cover letter.

• Virtual meet and greet. Meet with the Talent Acquisition Partner.
• A deeper conversation: We'll go into your experience and how you work, and you'll get a clearer picture of the team, the challenges, and what the role actually looks like day to day.
• Assignment‑specific interview. We want you to get an insight into some of the concrete work tasks or projects related to the role. You will be given a case to prepare prior to the interview, and at the interview, you will present the case to relevant colleagues from across Trackunit, who you’ll also work closely with in the job.
• If needed, throughout the process we will obtain references from former employers and do background checks for level specific, if you have not provided these yourself.
• Offer presentation and walk‑through. We’re lucky to have you!

Coming Together To Connect Construction

We’re committed to construction – one of the largest industries in the world. Over the past two decades, Trackunit has been pioneering technological progress within construction. Today, we are not only a leading IoT provider but a thought leader, supporting and shaping the agenda for an entire industry on a global scale.

We believe in taking a people approach in everything we do. Being human‑centric is not restricted to our products – it’s a way of life at Trackunit. We’re proud to be a truly global team. Our colleagues get together in hubs spread across the globe, but we embrace the idea of working remotely and in environments that inspire you. Everything we do, we do it to eliminate downtime and build the most useful industry for the world.

The question is: Are you in?