Senior Data Product Owner — Trusted Master Data at Kestra Holdings – Austin | Jobyssey

Lead with Purpose. Partner with Impact.
Kestra Financial is seeking a senior, governance-minded Data Product Owner to lead delivery of the Trusted Master Data initiative. This is our foundational program that establishes the golden source of record for the Account, Product Classification, Advisor, and Client domains across the enterprise. Reporting to the Manager of the Data Product Management Team, this role owns the mastered data backlog end-to-end and is accountable for the operational success of the Master Data Management platform on which every downstream data product, analytics use case, and advisor-facing application depends.
The Senior Data Product Owner for Trusted Master Data sits at the intersection of data engineering, business governance, and organizational change. Beyond delivering a working MDM platform on Profisee, this person leads the stakeholder journey that turns business leaders into accountable Data Owners and operational teams into trained Data Stewards. Success in this role is measured equally in technical delivery — match-and-merge precision, survivorship correctness, on-time domain rollouts — and in the maturity of the governance practice that surrounds it.

What you’ll Do:

Own the Trusted Master Data backlog end-to-end across the four mastered domains: Account, Product Classification, Advisor, and Client; including Profisee implementation, data governance and stewardship setup, MDM data protection and tokenization, and stewardship training and readiness workstreams.

Partner with the Product Manager and business stakeholders to maintain a multi-year, dependency-aware roadmap that sequences mastering work against downstream consumption needs across the Lakehouse, Performance Analytics, Advisor Compensation, and Regulatory data products.

Translate domain-level mastering requirements into clear epics and stories covering match-and-merge rules, search rules, stewardship workflows, survivorship and trust framework definitions, Initial Data Load (IDL) waves, ODS and Lakehouse publication, and production rollout phases.

Lead the governance process that elevates business leaders into named Data Owners and operational teams into trained Data Stewards — including Data Council facilitation, Key Data Element (KDE) definition workshops, business glossary development, and ongoing stewardship cadence design.

Manage Profisee MDM platform delivery in partnership with Kestra engineering, including match, merge, and survivorship configuration, search rule definition, stewardship UI enablement, and integration with downstream consumers via the ODS and the Lakehouse medallion (Raw / Clean / Model) architecture.

Represent business stakeholders in sprint ceremonies, ensuring stories meet the Definition of Ready before commitment and the Definition of Done before release focused on data quality thresholds, lineage documentation, PII handling, and entitlement validation.

Facilitate cross-functional refinement sessions with data engineers, data stewards, data quality engineers, delivery teams, source-system owners, and downstream consumers including the Lakehouse and Data Products workstreams.

Support release coordination, production cutover, parallel-run validation, and stakeholder communication for each mastered domain rollout.

Maintain a dependency register across upstream sources and downstream consumers, with named owners, due dates, and mitigation plans; escalate risks to the Product Manager proactively.
Deep Master Data Management domain knowledge — understands the difference between operational data, mastered data, and curated data products, and the role each plays in an enterprise data architecture.
Direct hands-on experience with a major MDM platform — Profisee strongly preferred; Informatica MDM, Reltio, Ataccama, or Stibo also considered — including match and merge rule configuration, survivorship logic, trust framework design, search rule definition, and stewardship workflow setup.
Strong working knowledge of medallion (Raw / Clean / Model) Lakehouse architecture and how mastered domains publish into ODS and Lakehouse layers; understands that MDM is upstream infrastructure for analytics, not an end in itself.
Strong stakeholder management and change management instincts — can guide business leaders through the transition from “I use the data” to “I am accountable for the data,” and operational teams into the discipline of data stewardship.
Excellent communicator across audiences — can frame MDM business value for executives, articulate match and merge precision tradeoffs with engineers, and lead Data Council conversations with business leaders without losing any of them.
Comfortable navigating governance ambiguity and source-system politics while maintaining delivery focus and stakeholder confidence.
Well-versed in Agile practices — Scrum ceremonies, backlog hygiene, sprint planning, and continuous improvement through retrospectives.
Ability to write or validate SQL queries for source profiling, match and merge testing, data reconciliation, and data quality validation.
Data Engineering and Architecture
Data Governance Council, Data Owners, and Data Stewards
Source System Owners (Investigo, Envestnet, Advisor Complete, BRACS, BSWP, KPWS, Salesforce, Addepar, custodial systems)
Business Intelligence and Analytics
Information Security and Data Privacy
Compliance and Supervision
Advisor Business Consulting and Field Management
Finance and Operations
Product Management (PM and other Product Owners)
External delivery partners as applicable

What You Bring:

Bachelor’s degree in Business, Finance, Information Systems, Data Analytics, Computer Science, or a related field; equivalent work experience will be considered.
5+ years of experience as a Product Owner, Product Manager, or senior Business Analyst delivering MDM, data governance, or master data programs in an Agile environment.
Proficiency in JIRA, Confluence, or equivalent backlog management and collaboration tools.
3+ years of direct hands-on experience with a major MDM platform; Profisee strongly preferred, but Informatica, Reltio, Ataccama, or Stibo also considered.
Demonstrated experience leading data governance setup: Data Council operations, Data Owner and Steward role design, KDE definition, business glossary management.
Working knowledge of Lakehouse / medallion architecture (Databricks, Snowflake, or equivalent) and how MDM publishes downstream to analytics consumers.
Familiarity with financial services data domains (Account, Advisor, Client, Product) strongly preferred.
Experience in financial services or wealth management environments is a strong plus.
Familiarity with regulatory reporting requirements in financial services (SEC, FINRA, FATCA) is a plus.

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