MDM Data Engineer

Job description

This is an implementation role, not an advisory one. You''ll write code, configure match rules, and debug pipeline failures.

What You''ll Do

· Configure and tune Profisee match and survivorship rules for Client and Advisor entities (probabilistic + deterministic matching, confidence thresholds, conflict resolution).

· Build and maintain the integration between Databricks Delta Lake and Profisee — ingestion of staging records into Profisee, and write-back of golden records to the Lakehouse.

· Set up the Profisee stewardship portal for data steward workflows — exception queues, match review, and record correction.

· Work with upstream pipeline engineers to ensure records are correctly partitioned and flagged before they hit the MDM layer.

· Monitor MDM pipeline health — match rates, queue depth, golden record lag — and fix issues when they arise.

· Document match rules, survivorship decisions, and integration patterns for the team.

Must-Have

· 3+ years with Profisee MDM — you''ve implemented it, not just administered it. You know match rules, survivorship policies, and Profisee Connect.

· Strong SQL and Python — you can write and debug pipeline code independently.

· Profisee integration experience — connecting Profisee to an external data platform (Databricks, Snowflake, SQL Server, or equivalent) via API or connector.

· Match/merge configuration — candidate generation, scoring, threshold tuning, and survivorship.

· Cloud environment experience — AWS or Azure.

Nice to Have

· Databricks / Delta Lake experience (DLT, MERGE, Change Data Feed).

· Financial services domain knowledge — client data, advisor data, accounts.

· Experience with other MDM tools (Reltio, Informatica, Semarchy).

· Kafka / event-driven pipeline experience.