Tech Data Product Owner

Kestra HoldingsTempe, AZ

About The Position

Kestra is seeking a customer-focused, outcome-driven Data Product Owner to lead the development and adoption of trusted master data as a core enterprise capability. Reporting to the Manager of Data Product Management, this role translates business needs into scalable master data products and drives execution across engineering, governance, and business stakeholders. This role sits at the intersection of strategy, governance, and delivery. The successful candidate will own master data domains data products, ensuring they are trusted, governed, and actively consumed across analytics, reporting, operational, and AI use cases. The Product Owner serves as a key liaison between business leaders, data governance, and technical teams, ensuring master data solutions align with Kestra’s business objectives and deliver measurable value.

Requirements

  • Bachelor's degree in Business, Information Systems, Computer Science, Data Analytics, or related field; equivalent work experience will be considered.
  • 3+ years of experience as a Product Owner or Business Analyst supporting data platforms, enterprise reporting, or analytics solutions in an Agile environment.
  • Hands-on experience with cloud-based data platforms, ideally within the Microsoft Azure ecosystem (e.g., Azure Data Factory, Azure Synapse, Data Lake) and Databricks.
  • Strong familiarity with data warehousing concepts, data ingestion processes, and data product lifecycle management.
  • Proficient in using product and collaboration tools such as JIRA and Confluence for backlog management and team communication.

Responsibilities

  • Own the definition, evolution, and success of trusted master data products (e.g., Client, Advisor, Account, Firm, Product) as reusable enterprise assets.
  • Partner with Data Governance and business Data Owners to define golden record definitions, survivorship rules, and domain-specific data standards.
  • Drive adoption of master data by downstream consumers (Analytics, Reporting, AI, Operations, Compliance), ensuring master data is fit-for-purpose.
  • Define and track success metrics for master data products (e.g., data quality scores, match rates, duplicate reduction, downstream consumption, business issue reduction).
  • Act as the primary liaison between business users, data analysts, data engineers, and developers to ensure consistent understanding and delivery of business needs.
  • Coordinate dependencies and share learnings across the Product Owners and teams to support enterprise alignment across the data ecosystem.
  • Collaborate with the release manager and QA to support production deployments and communicate release notes to business stakeholders.
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service