Technical Product Manager

Job Title: Technical Product Manager
Location: Atlanta Georgia 30328-5588
Duration: 4 months on contract

About the Role
We are seeking a highly driven Technical Product Manager to own and evolve our enterprise Data Governance Platform. In this role, you will sit at the intersection of business strategy, data engineering, and AI innovation, translating complex regulatory and data quality requirements into a clear, compelling product roadmap that your engineering teams can execute against. You will work daily with Collibra, Databricks Unity Catalog, and multi-cloud infrastructure to drive the next generation of governed, trustworthy, and AI-ready data assets.

Key Responsibilities
Product Strategy & Roadmap
Own the end-to-end product roadmap for the data governance platform, from ideation through delivery and adoption.
Envision and prioritize best-in-class features for metadata management, data lineage, access controls, data quality, and policy automation.
Champion a user-first mindset - translate nuanced business pain points into tangible product capabilities that deliver measurable value.
Stakeholder Engagement & Storytelling
Serve as the primary liaison between business stakeholders (Data Owners, Compliance, Analytics, Legal) and the engineering team.
Craft clear, compelling narratives using data and visualizations to communicate platform capabilities, adoption metrics, and strategic direction to executive audiences.
Lead discovery workshops and requirement-gathering sessions to surface governance needs across business domains.
Technical Requirements & Engineering Handoff
Decompose high-level business requirements into well-defined epics, user stories, and acceptance criteria ready for engineering sprint planning.
Collaborate with architects and data engineers to evaluate technical feasibility, dependencies, and trade-offs for governance platform features.
Maintain tight feedback loops with engineering during delivery, this includes reviewing PRDs, attending standups, and unblocking delivery impediments.
Data Governance Platform Operations
Act as the product owner for all governance platform requests — triaging, prioritizing, and resolving incoming asks from business and technical teams.
Drive the configuration, adoption, and continuous improvement of Collibra.
Own the Databricks Unity Catalog strategy — including schema governance, row/column-level security, attribute tagging, and data sharing policies.
Partner with cloud platform teams to align governance capabilities across AWS, Azure, and GCP environments.
AI-Driven Governance
Drive the integration of AI/ML capabilities into the governance platform — including LLM-powered metadata enrichment, automated classification, and smart lineage detection.
Evaluate and recommend AI tooling (e.g. Azure AI Foundry, Amazon Bedrock, Databricks AI) that can accelerate governance automation.
Stay abreast of emerging AI governance standards (EU AI Act, model cards, responsible AI frameworks) and incorporate them into platform strategy.
SQL, ETL & Pipeline Governance
Leverage deep SQL proficiency to independently investigate data pipeline issues, validate data quality rules, and diagnose lineage breaks.
Work hands-on with ETL pipelines (Spark, dbt, ADF, or equivalent) to understand pipeline architecture and translate technical failures into governance requirements.
Define and enforce data contracts, SLAs, and quality thresholds across ingestion and transformation layers.

Required Qualifications
8 years of experience in product management, data engineering, or a related technical role, with at least 3 years focused on data governance or data platform products.
Hands-on experience with enterprise data governance tools such as Collibra or any similar data governance tool.
Strong working knowledge of Databricks Unity Catalog - including data access policies, attribute tagging, and Delta Sharing.
Demonstrated experience working on multi-cloud infrastructure platforms (AWS, Azure, GCP) and understanding cross-cloud data governance challenges.
Advanced SQL proficiency — able to write complex queries, debug pipeline failures, and validate data quality rules independently.
Practical experience with ETL/ELT pipeline technologies (e.g. Apache Spark, dbt, Azure Data Factory, AWS Glue, Airflow).
Proven ability to translate ambiguous business requirements into structured, engineering-ready user stories and acceptance criteria.
Exceptional storytelling and communication skills — able to simplify complexity for both executive and technical audiences.
Strong understanding of AI/ML concepts and their application to data governance use cases (automated classification, PII detection, lineage inference).
Experience running agile product delivery including backlog grooming, sprint planning, and stakeholder demos.

Preferred Qualifications
Experience with data mesh or data fabric architecture patterns.
Familiarity with regulatory frameworks such as GDPR, CCPA, HIPAA, and their technical implementation in data platforms.
Exposure to AI governance platforms and responsible AI principles (model lineage, bias detection, explainability).
Knowledge of metadata standards such as Collibra, Open Lineage, Apache Atlas.
Certifications in cloud platforms (AWS, Azure, GCP) or data governance tools (Collibra, Databricks).

Tools & Technologies

Collibra / Alation Databricks Unity Catalog Azure AI Foundry Apache Spark / dbt SQL (Advanced)

AWS / Azure / GCP Azure Data Factory Apache Airflow Open Lineage Python / PySpark

What We Value
• You ask 'why' before 'how’ and can zoom in and out between strategic and technical perspectives.

• You prioritize ruthlessly and measure success in terms of outcomes, not output.

• You can tell a compelling data story to leadership (VP, SVP)

• You are energized by the potential of AI to transform data governance and actively look for opportunities to integrate intelligent automation into platform workflows.

• You operate as a true partner to engineering, design, and business