How to land a job in Data Governance
#23 Do the transition
Hello 😀
You want to transition into Data Governance? You’re already in the data field, or close to it as business analyst for example, but you don’t know what to do to get a job in Data Governance.
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Agenda
Study stuff
Prepare your bullets
Ace the interview
Study stuff
First, you need to “look well”. I mean your online profile should be impeccable. There’s no excuse today for not doing it, all HR teams are checking us online first. Plus everything is doable from home nowadays.
Here’s your checklist :
✅ Upgrade your LinkedIn - photos, headline, description, experience. Everything must be up to date, there’s ton of articles explaining how to do it properly.
✅ Relationships & network - connect with data governance professionals and ask them questions about the field and what they do. You can also comment posts on this topic and start networking from there.
✅ Events - participe to online events or webinars related to this topic (it can be data quality or even webinars from data management vendors). You’ll learn the jargon.
✅ Online communities - join Slack communities from your country, you’ll see what problems people have when working with data and you’ll network. For example in France, I keep recommending the Modern Data Network.
Now you can study to anticipate your future interviews.
Know your basics
Read specific books like the DAMA-DMBOK or guides on Data Management, find resources on the internet in order to study some key concepts :
Data Governance foundations : definition, benefits, key pillars, roles & responsibilities, operating models, maturity models, KPIs
Data Quality Management : key dimensions, issue management, remediation workflows and monitoring
Metadata Management : types, lineage, impact analysis
Master Data vs Reference Data : difference and usefulness, MDM tools and workflows
Data Modeling : types, main techniques including hierarchical, network, relational, entity-relationship, object-oriented
Data Privacy & Compliance : data classification, access policies, retention
Data Integration : journey from data creation to archival/deletion, ETL, ELT, APIs, data mesh
Data Governance tools : make or buy considerations, business glossary, data catalogs, data quality management, data protection
💎 Bonus : Explain the difference between Data Governance vs. Data Management vs. Data Strategy !
You need to know and understand the concepts, not be an expert of each of them - all these questions will have to be debated with IT architects, security experts, etc.
Prepare your bullets
Your goal is to make the interviewer thinks that you’re already part of the company, doing the job. It means that you're projecting yourself into the job, which is very positive !
Give concrete examples
… of you leading a data project. Employers want to see that you can take leadership and drive data initiatives forward.
It doesn’t have to be the perfect Data Governance initiative, it can be something related to it while you were a data analyst or business expert.
✅ Examples from work experience :
Led a data cleanup project to improve CRM data quality, reducing duplicate records by 40%
Designed as business expert a local framework, defining data ownership and access policies
Helped solving data-related issues in dashboards used by your team
Even a side project is convincing
If you’re struggling with “I don’t have Data Governance experience,” create your own! There’s a lot of datasets publicly available on which you could do a small project.
🚀 Ideas for DIY Data Governance projects :
Audit a dataset (public data, personal finance, etc.) and document data quality issues & remediation plans
Create a mock Data Governance policy for a fictional company : what are the data domains? who owns what? what rules apply?
Analyze data lineage for a small dataset : track where data originates and how it changes over time
Mockup what you’d do in the first 6 months
Hiring managers love candidates who show initiative and structured thinking. Can’t blame them !
Before your interview, prepare a "First 6 months Plan".
To do this, you should first make research about the company :
What are their latest business news?
Can you translate these into data requirements?
From what you read online (their blog, competitors website, latest LinkedIn posts from the data team, etc.), what do you think of their maturity level?
Based on these elements, you can setup a high level 6-months plan.
🗓️ Example of a 6-Month Plan :
🔹 Month 1-2 : Conduct a Data Governance assessment (Who owns data? What are the biggest data pain points?)
🔹 Month 3-4 : Implement quick wins (Define critical data elements, create a basic glossary) while building first foundations
🔹 Month 5-6 : Roll out automated data quality monitoring and present a roadmap for long-term governance
You should also prepare on each phase how you’re going to do it. For the assessment, the interviewer could ask you to detail it : number of people to interview, documents to be reviewed, tools you’ll need, etc.
🔍 Tip #1 : Showing that you’ve thought through this will make you stand out, even against more experienced candidates !
Ace the interview
Expect "What would you do if..." questions. It’s the only way for the interviewer to test you, usually they do it on situations currently encountered by the company.
Questions of this type are usually such as :
🔹 "Our company has no Data Governance framework, where do you start?"
🔹 "Data quality is a mess currently, especially with our customer data, what steps do you take?"
🔹 "Stakeholders don’t see the value of Data Governance, how do you convince them?"
Solving common scenarios
Structure your answers using STAR (Situation, Task, Action, Result).
Let’s take the last question as example :
"Stakeholders don’t see the value of Data Governance, how do you convince them?"
Good Answer with STAR Method :
🟢 S – Situation : Business leaders can view Data Governance as a bureaucratic burden rather than a value driver. Here you can also ask questions to clarify the situation : which stakeholders are we talking about? what do they say precisely? what are their pains when they use data?
🟡 T – Task : The goal is to demonstrate the tangible business value of Data Governance in a way that will resonate with each stakeholder group : executives, analysts, and IT teams.
🟠 A – Actions :
Identify pain points for each stakeholder :
Analysts were frustrated with reporting errors due to poor data quality.
IT was spending too much time fixing ad-hoc data issues.
Present real-world impact :
Use data quality metrics to show that inaccurate data is causing delayed decision-making & lost revenue.
Show a case study where governance reduced manual data cleanup efforts by 50%.
Start with a small win :
Pilot a data quality dashboard for one key business unit, fixing common errors & reducing mismatched records.
🔴 R – Result : The small win will highlight ROI, which will build buy-in for a larger data governance initiative.
Ask smart questions at the end
When I was hiring for my customers, candidates who didn't ask any questions never got past the 2nd stage of the recruitment process. Because it’s a big red flag.
Here are some examples of great questions to ask :
What are the biggest data governance challenges this company faces?
What would you look at at the end of my first year to review my performance?
What would you have done differently if you could restart at your position?
How are decisions taken in the company? Is data used to this end?
👉 Good questions show you're serious about the role and thinking ahead.
See you soon,
Charlotte
I'm Charlotte Ledoux, freelance in Data & AI Governance.
You can follow me on Linkedin !