Technical Product Owner

TechStar Group; Dallas (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

TechStar Group seeks an experienced Technical Product Owner for the Data Platform to own the data engineering backlog, drive Agile delivery, and govern the Silver, Gold, and Platinum layers in Databricks.

You will partner with data engineers, architects, governance teams, and stakeholders to translate requirements into actionable work, define KPIs, and ensure quality data products across the platform.

Qualifications

• Proven experience as Product Owner and Scrum Master in Agile teams.
• Strong SQL, data modeling, ETL/ELT, and data governance experience.
• Experience with medallion architecture (Silver/Gold/Platinum) and Databricks.
• Excellent stakeholder management and communication skills.

Responsibilities

• Own and manage the data engineering team's Jira backlog with clear epics and stories.
• Define data product roadmap and track delivery status to leadership.
• Serve as Scrum Master for data engineering team: plan stand-ups, sprints, reviews.
• Promote Agile best practices and remove impediments.
• Ensure data products meet business requirements and quality standards.
• Govern the Silver, Gold, Platinum data promotion process in Databricks.
• Collaborate with governance, data architects, analysts and stakeholders.

Skills

Product Ownership

Scrum Master

Agile delivery

Jira

SQL

Stakeholder management

Data governance

Medallion Architecture

Tools

Databricks

Job description

We are seeking an experienced Technical Product Owner- Data Platform to support the development and governance of an enterprise data platform built on Databricks.

The successful candidate will be responsible for owning the data engineering product backlog, driving Agile delivery, facilitating Scrum ceremonies, and ensuring that high-quality data products are developed and promoted through the Silver, Gold, and Platinum layers of the enterprise data platform.

This role requires a strong combination of technical data knowledge, Product Ownership, Scrum Master capabilities, Jira expertise, SQL proficiency, stakeholder management, and data governance experience.

Key Responsibilities

Product Ownership

• Own and manage the data engineering team's Jira backlog, ensuring work is clearly defined, prioritized, and aligned with business objectives.
• Create and maintain well-defined epics, features, user stories, acceptance criteria, and technical requirements for data engineering initiatives.
• Prioritize backlog items based on business value, technical dependencies, delivery risk, regulatory requirements, and strategic priorities.
• Develop and maintain a rolling data product roadmap, communicating priorities, milestones, dependencies, and delivery status to leadership and stakeholders.
• Partner with business stakeholders, data engineers, data architects, data analysts, and governance teams to translate business requirements into actionable technical work.
• Define and track KPIs and success metrics related to data product quality, coverage, usability, timeliness, and adoption.
• Ensure delivered data products meet agreed business requirements and quality standards.

Data Product & Medallion Architecture Governance

• Govern the end-to-end Silver, Gold, Platinum data promotion process within the Databricks environment.
• Ensure data products meet defined quality, completeness, accuracy, consistency, lineage, and business-alignment criteria before promotion between layers.
• Work closely with data engineering and architecture teams to define standards and acceptance criteria for each medallion layer.
• Validate that Gold and Platinum data products are appropriately modeled and aligned to business use cases.
• Support documentation of data products, data models, business definitions, transformations, and data quality rules.
• Identify data quality issues and coordinate remediation with engineering and data governance teams.
• Promote consistency in data product development, ownership, documentation, and lifecycle management.
• Serve as Scrum Master for a dedicated data engineering team.
• Sprint Planning
• Daily Stand-ups
• Sprint Reviews/Demos
• Sprint Retrospectives
• Remove impediments and proactively identify issues that may impact sprint commitments.
• Protect the engineering team from scope creep, unplanned work, and unnecessary interruptions.
• Track sprint progress, velocity, capacity, dependencies, and delivery risks.
• Identify and elevate blockers and risks to appropriate leadership in a timely manner.
• Promote Agile best practices and foster a culture of continuous improvement, accountability, transparency, and collaboration.
• Work with the Product Owner and engineering team to ensure realistic sprint commitments and predictable delivery.

Technical Requirements

• Strong understanding of Medallion Architecture, particularly Silver, Gold, and Platinum data layers.
• Strong SQL skills, with the ability to:
• Write and interpret complex SQL queries.
• Validate data models and transformations.
• Perform data quality and reconciliation checks.
• Support technical and business documentation.
• Understanding of data modeling, ETL/ELT pipelines, data quality, metadata, lineage, and data governance.
• Strong Jira proficiency, including backlog management, epic/story creation, acceptance criteria, sprint planning, and sprint tracking.
• Experience working with Agile/Scrum methodologies in a technical engineering environment.

Required Experience & Qualifications

• Proven experience serving in both Product Owner and Scrum Master capacities for an Agile engineering/data engineering team.
• Strong experience managing technical backlogs and translating business requirements into actionable engineering work.
• Demonstrated experience writing high-quality epics, user stories, acceptance criteria, and technical requirements.
• Experience managing delivery roadmaps and communicating status to senior leadership and business stakeholders.
• Strong stakeholder management and communication skills.
• Experience working with cross-functional teams including data engineers, architects, analysts, governance teams, and business users.
• Strong analytical and problem-solving capabilities.
• Ability to understand technical data concepts and effectively communicate them to both technical and non-technical stakeholders.