Between Data Analysis and Data Engineering: Analytics Engineer


Chris Rieckmann is an Analytics Engineer and Software Engineer at AMBOSS. He shared what he has been working on, and what someone can expect in the Analytics Engineer role when joining the Data team. Join the Business Intelligence team as our next Analytics Engineer!

Why did you decide to become an Analytics Engineer?

I studied physics, then worked as a Software Engineer at an Artificial Intelligence company where I worked on many data related projects. I joined AMBOSS as a Data Analyst in 2022, focussing on improving the data warehouse. I found this interesting, and there was a lot of work to do, so that’s how I got into the Analytics Engineer role.

What is an Analytics Engineer?

The job of an Analytics Engineer is to make sure that data can be easily used for analysis. We do this so Data Analysts and other stakeholders can use data more effectively, and involves integrating data from different sources.

For example, combining revenue data with email campaign data in a single table allows the campaign manager to get insights much faster, and with simpler queries. Displaying the data in this way also requires standardizing naming and converting everything to the same units.

To ensure that the data is useful, it’s also important to monitor and improve the data accuracy, simplify the transformations, investigate data inconsistencies, and optimize query performance. 

What is unique about this role in relation to other data or engineering roles? Can you give me an example?

The boundaries are blurry, but in a way, Analytics Engineers sit between the Data Engineers and Data Analysts, and help Data Analysts to do their job more effectively. Comparing the roles, I would say that Data Analysts work more closely with stakeholders and do specific in depth analyses. Data Engineers focus more on things like bringing data in from different data sources. 

As the company grows and the data warehouse becomes more complex, there’s a lot of work that needs to be done between the data arriving in the data warehouse and it being ready for analysis. This requires both data analysis skills and applying software engineering techniques to ensure quality and reliability.

Why is it challenging and what can people look forward to working on generally?

For me, it’s interesting to be exposed to the challenges of working with larger datasets. Many of the tools for working with large datasets are also new and constantly improving, as it’s a very fast changing industry. I also noticed that a lot of the teams at AMBOSS are using data heavily, and I can see that my work is really helping them.

What does a typical day look like for an Analytics Engineer?

I’m in the company’s Data Team together with Data Analysts, Data Engineers, and Data Scientists. We have a meeting on Mondays to discuss the plan of the week and a knowledge sharing session on Fridays. To give a concrete example of a project, I recently worked on adapting the Data Warehouse to a new payment system. Sometimes I also work on data analysis or data engineering projects.

A lot of us in the Data Team work remotely from different cities, but we often meet up in person. We meet in the Berlin office, or at the office in Sardinia. A few months ago we went to Sardinia, which was nice.

In terms of tools, we mostly use BigQuery, Dataform and Airflow. For creating interactive dashboards, we use Metabase, which is also used by other teams to visualize data.

What do you enjoy about it?

I find it interesting to work with different datasets, and to have access to effective tools for working with the data. The team is also great — everyone is friendly and helpful. When working on data analysis tasks, I also enjoy working with different people in the company and helping them make decisions based on data. I find that quite refreshing.

In addition to the knowledge sharing sessions, we also just started doing data hackathons, where we get to work on more explorative topics for a day. Many useful ideas have come out of that, and it’s also educational and fun.

Every day there are thousands of scheduled data transformations and Terabytes of data processed, combining product, financial and marketing data to enable the many different teams of the company to operate more efficiently. There’s lots of stuff to work on at AMBOSS for an Analytics Engineer. 

We’re hiring for an Analytics Engineer. If you enjoyed this post, and are interested in being part of the AMBOSS team, apply today!