Profisee MDM Engineer

About the Role

You'll be the hands-on MDM engineer on a data modernization program for a large financial services client. The platform is built on Databricks and Delta Lake; your job is to own the Profisee MDM layer — configure it, connect it, and keep golden records flowing cleanly into the downstream warehouse.

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.

You're a Good Fit If…

* You can configure a Profisee match rule from scratch and explain why you set the thresholds where you did.

* You've debugged a golden record that wasn't writing back correctly and can walk through how you found the issue.

* You don't need someone to hand you an architecture diagram before you can ask good questions.

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