Specialist, Data Analytics
Posted Sep 2, 2026 · We last checked this listing on Oct 6, 2026
Likely interview questions for this role
Written from this job description, not a generic list. Each one notes what the interviewer is really checking.
About your past
Tell me about a time you turned a vague business request into clear functional requirements.
What they are checking: Whether they can act as the bridge between business needs like KYC and the technical MDM design.
Describe a time you led other engineers through a technical decision you were accountable for.
What they are checking: Whether they can act as the technical leader the role calls for, guiding design choices rather than only coding.
What would you do
The KYC team says onboarding is delayed because client data is wrong in MDM. How do you find the cause?
What they are checking: Whether they trace a data quality issue back through ingestion and transformation to its real source.
A downstream team changed how they read your MDM feed without telling you, and their reports broke. How do you handle it?
What they are checking: Whether they fix the immediate problem and then put contracts or communication in place to prevent repeats.
How do you balance delivering new MDM features with fixing the data quality debt you already have?
What they are checking: Whether they protect trust in master data while still meeting business demands for new capabilities.
About the work
Walk me through how you would design the data flow for a master party record coming from several source systems.
What they are checking: Whether they understand matching, survivorship and golden record design in Master Data Management, not just moving data.
How would you decide which source wins when two systems disagree about a client's legal name or address?
What they are checking: Whether they can define survivorship rules with business owners instead of making silent technical choices about client data.
What data quality checks would you build into an MDM pipeline before data gets distributed to downstream systems?
What they are checking: Whether they catch bad data before it spreads to reporting, onboarding and regulatory processes across the enterprise.
How would you model the relationship manager hierarchy so it stays accurate when people change roles?
What they are checking: Whether they think about how hierarchies change over time and how that affects reporting and access downstream.
Write out loud a SQL approach to find likely duplicate client records across two tables.
What they are checking: Whether they have hands-on SQL skill and understand that matching needs fuzzy logic, not just exact joins.
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Practice this out loudThe full job description
As published by Northern Trust.