Globally consistent and high quality data, that's the work of a Data Steward

Lara Meester - tijdelijk
Lara Meester - Data Analyst
Lara Meester
Data Analyst
Reading time3.5 minutes

Lara Meester started working as a Data Analyst at Rabobank two years ago, and quickly developed into a Data Steward. Within this role, she works on a large customer data project to clarify Rabobank’s global data. ‘This will make our colleagues’ work much easier.’

“I don’t have a background in finance, but I was able to start as a junior Data Analyst via a traineeship. The bank and I immediately ‘clicked’, both with the work and the other colleagues. Since then, I’ve worked my way up to the position of Data Steward. Another Steward left, and I thought that was a good moment to grow into that position. My manager had the same idea. That’s one of the things I like about Rabobank: you get the support you need to realize your ambitions. Data analysis is a great job, but the work of the Data Steward is also fascinating to me. As an analyst, you focus more on the differences between the new system and the old one. As a data steward, you think about whether those differences are actually an improvement.”

Dozens of systems

“At the moment, I’m working as Data Steward on a project where we’re migrating the different customer systems to a single customer system worldwide. That’s as interesting as it is complex. Right now, the bank is using all sorts of customer systems; some are even specific to the region. The data from all those systems flow to our data warehouse, which our team is responsible for. But the data from a customer system in Chile, for example, could be defined differently than in Utrecht or New York. In one system, the main office in the country might be the location address, while in another country it might be the local office. Some systems might include certain data elements, while others don’t. In short: the data is incomplete and unclear.”

"As Data Steward, I help decide what those data definitions will be. That standardization will help improve the quality of the data." 
Lara Meester

Higher quality

“If we work with the same customer system around the world, then we’ll only need to connect a single system to our data warehouse. That’s much more efficient. Plus, we’ll work with the same data and the same definitions everywhere. As Data Steward, I help decide what those data definitions will be. That standardization will help improve the quality of the data. This means the Data Quality team – which is responsible for correcting the data – won’t have as much work to do. The reporting teams will also be happy with the higher quality. They’ll be able to submit more complete, better-quality reports to the Dutch and European central banks.”

Learning from each other

“You can only complete a big project like that through good teamwork. During the test phases for the new system, we have an update meeting every morning with the reporting teams, the implementation manager and IT. I learn a lot from that. And in our own team, we constantly keep each other up to date through weekly meetings. The team consists of around 25 Data Analysts, Data Stewards, Product Owners and Implementation Managers. Every colleague has his or her own projects, but everyone is glad to help if you have a question or would like to spar with someone. I think that’s important for the quality of our work, and for the atmosphere.”

Ideal mix

“Rabobank welcomes hybrid working so I mainly talk to my colleagues online. That meant that I was able to work remotely from Spain for several weeks. I think working part of the time from home and part of the time at the office is an ideal mix. The home office facilities are great; the bank’s provided a sit-stand adjustable desk and an additional screen.”


“Why do I enjoy my work? At Rabobank, you work with so much data; that makes the work extremely complex. What are the critical data elements? What about the governance aspects? How are the data used for analysis? How do you keep the quality of data as high as possible? I love solving puzzles, so these are the kinds of questions I like to sink my teeth into. It’s also interesting to work with a programming language like SQL. I can use an SQL query to look for the specific data that I need. I also work with Knime, which allows you to automate data comparisons. I learn something new every day in this place, so it’s a perfect fit for me.”