What to expect on your Data Product Manager interview?
If you’re looking into a role in data product management you know that these roles are a unique balancing act. This article covers the 4 areas that will likely be covered in any Data PM interview.
What to expect on your Data Product Manager interview?
If you’re looking into a role in data product management you know that these roles are a unique balancing act. Interviews for these roles will:
- Challenge your knowledge of the data platform ecosystem and related tooling
- Probe your experience with both basic (SQL) and advanced (ML) analytics techniques
- Assess your ability to discover customer problems and rapidly prototype solutions that deliver customer value
- Test your experience with leading and coordinating highly-technical teams in an agile framework
What if I don’t have all the requirements?
The truth is Data Product Management is a very nascent role, don’t worry if you don’t have all the prerequisite knowledge and experience prior to the interview. We find that Product Managers with some data or analytics chops or Data Analytics professionals with business or communications skills can be great candidates for making a lateral transition. But there a couple key areas you’ll want to brush up on…
How to prepare for the technical side of the Data Product Manager interview
The technical side of the Data Product Manager interview will usually cover topics like data platforms, data science, and SQL basics. Be sure to brush up on the current data platform ecosystem, which may include data warehousing, data lakes, and the data mesh architecture. If these seem intimidating or over your head, don’t worry! Focus on the business impact that centralizing data for internal use has, read up on a couple real-life examples, and identify what kinds of challenges these teams are facing.
“Focus on the business impact that centralizing data for internal use has, read up on a couple real-life examples, and identify what kinds of challenges these teams are facing.”
Interesting resources for brushing up on the data platform ecosystem
The following are helpful guides for learning more about the current data platform ecosystem:
- The Self-Service Data Roadmap: Democratize Data and Reduce Time to Insight, by Sandeep Uttamchandani
- Data Mesh, by Zhamak Dehghani
- The Best in Data Engineering list, The Data PM
What other tools do you use?
SQL, executed in a database client like DBeaver, DataGrip, etc is the Data Product Manager’s best friend for ad-hoc analysis. Scripting languages like python, while not necessary, may be a helpful leg up and demonstrate technical aptitude. Jupyter notebooks are the common tooling for basic exploratory data analysis and having an example of one in your portfolio, even if you’re following a tutorial, would be a big advantage.
How to prepare for the “product” side of the Data Product Manager interview
Your would be coworkers want to know that they can trust your ability to lead the team, identify which problems to work on, and help their fledgling products go-to-market successfully. In order to adequately prepare for the business or product side of this interview, you’ll want to demonstrate experience and/or aptitude for the following:
- Agile best practices, including scrum ceremonies, the use of jira to manage sprints, setting and aligning on OKRs
- Problem Discovery, including how to find the “real” problem behind customer issues
- Solution design, identifying solutions that meet the customers need in the simplest and quickest way first
What about the tools?
While most organizations are tool agnostic, it would be helpful to learn or highlight your experience with agile project management tools such as jira, and confluence. If you’ve worked in a remote setting, or worked with international teams, highlight tools and learnings from these experiences where applicable — i.e., we found Async Poker to be a great way to conduct grooming and story point estimation with an globally distributed team.
