Job Description & Details
This is a heavy-duty data product management role sitting inside a risk management organization, specifically building out data pipelines and products for Anti-Money Laundering (AML) teams. If you enjoy wrangling complex enterprise data requirements and translating them into actionable roadmaps for engineering squads rather than building consumer-facing apps, this one is worth a serious look.
What You'll Actually Be Doing
Your typical week will involve acting as the glue between data providers, upstream system owners, and the AML modeling and investigation teams who desperately need clean, reliable data. You'll spend a good chunk of your time managing Jira boards, unblocking engineering teams, and ruthlessly prioritizing the backlog. Expect to navigate messy stakeholder dynamics where everyone thinks their data request is P0, requiring you to stand your ground with solid data sourcing logic and realistic delivery timelines.
The Core Tech Stack
While you won't be writing the code yourself, you need to be deeply conversant in data engineering concepts. You live and breathe Jira for Agile delivery, but the real meat of the job requires a strong grasp of data pipelines, enterprise data architecture, data quality, and consumption patterns. If you don't know the difference between how data is sourced, structured, and accessed in a modern data stack, you'll struggle to earn the respect of the data engineers on your team.
Interview Expectations
Expect the hiring manager to drill down into a past project where you had to manage conflicting priorities between data consumers and data providers, wanting to know exactly how you made the tradeoff decisions. They will likely ask you to explain how you handle a scenario where data quality issues are actively breaking downstream AML models, and they'll be secretly looking for your ability to manage panic, communicate transparently, and partner directly with engineering to ship a hotfix without burning out the team.
Application Advice
Make sure your resume doesn't read like you just managed mobile UI or generic web apps. You need to heavily emphasize keywords like Data Product Management, enterprise data solutions, stakeholder alignment, and Agile backlog prioritization. Highlight any specific experience you have in highly regulated spaces like Risk, AML, Compliance, or Financial Services to make it past the initial ATS screening.