Description

• Own the product vision, roadmap, backlog, and delivery priorities for Databricks migration and modernization initiatives.
• Partner with Databricks architects and engineering teams to translate the target-state architecture into executable epics, features, user stories, milestones, and release plans.
• Lead discovery workshops with business stakeholders, data owners, application teams, governance teams, and source-system SMEs to understand current-state workloads, pain points, dependencies, and migration requirements.
• Build and maintain the prioritized migration backlog covering:
  • Legacy platform/workload migration
  • Data ingestion and transformation
  • Data-quality remediation
  • Governance and metadata
  • Security and access
  • Reporting and analytics dependencies
  • Downstream integrations
  • Cutover and decommissioning activities
• Define clear business requirements, functional requirements, user stories, acceptance criteria, Definition of Ready, and Definition of Done.
• Work closely with architecture and engineering teams to assess migration complexity, sequencing, technical dependencies, risks, and business value.
• Prioritize workloads for migration based on business criticality, technical readiness, regulatory requirements, complexity, cost, dependencies, and expected value.
• Drive migration planning from assessment and rationalization through development, testing, reconciliation, cutover, production validation, and legacy decommissioning.
• Coordinate migration waves and release plans across multiple applications, data domains, source systems, and downstream consumers.
• Ensure business requirements are aligned with the Databricks target-state architecture, including Medallion Architecture (Bronze, Silver, Gold), Delta Lake, Unity Catalog, data-quality controls, security, and governed consumption patterns.
• Partner with Data Governance teams to ensure migration requirements incorporate:
  • Data ownership and stewardship
  • Data classification
  • Metadata
  • Lineage
  • Data quality
  • Retention
  • Privacy
  • Access-control requirements
• Ensure functional and non-functional requirements related to security, performance, scalability, reconciliation, auditability, availability, compliance, and operational support are captured in the backlog.
• Work with architects, engineers, and business SMEs to identify and resolve requirement gaps, cross-team dependencies, data issues, and migration blockers.
• Coordinate source-to-target validation and ensure appropriate acceptance criteria are established for:
  • Data completeness
  • Data accuracy
  • Reconciliation
  • Transformation logic
  • Historical-data migration
  • Performance
  • Downstream consumption
• Partner with QA / Quality Engineering teams to define business acceptance criteria and ensure appropriate functional, integration, regression, data-validation, and migration testing.
• Lead backlog refinement, sprint planning, release planning, product demos, stakeholder reviews, and retrospectives in partnership with Scrum Masters and engineering leads.
• Make timely prioritization and scope decisions while balancing business value, regulatory obligations, technical debt, migration risk, and delivery timelines.
• Track migration progress, risks, blockers, dependencies, and decisions and provide clear reporting to business and technology leadership.
• Define and track product and migration KPIs such as:
  • Workloads migrated
  • Migration velocity
  • Data-quality metrics
  • Reconciliation success
  • Defect leakage
  • Platform adoption
  • Legacy workloads decommissioned
  • Business acceptance
  • Cost and performance improvements
• Coordinate User Acceptance Testing and obtain business acceptance / sign-off prior to production migration and cutover.
• Support migration cutover and production-validation activities and help prioritize defects or issues based on business impact.
• Partner with the Databricks Architect to ensure delivery remains aligned with enterprise architecture, governance, security, and engineering standards.
• Collaborate with vendors and system integrators and ensure deliverables align with product priorities, requirements, timelines, and acceptance criteria.
• Communicate product status, roadmap changes, risks, dependencies, and migration outcomes to both technical teams and senior business stakeholders.

Basic Qualifications

• Minimum 8+ years of overall experience in Product Ownership, Product Management, Business Analysis, Data/Analytics delivery, or enterprise technology transformation.
• Minimum 4+ years of experience as a Product Owner / Senior Business Analyst / Product Manager supporting complex enterprise technology or data-platform initiatives.
• Demonstrated experience supporting large-scale data migration, cloud modernization, data-platform transformation, or analytics modernization programs.
• Strong understanding of enterprise data platforms and modern data architectures.
• Working knowledge of Databricks, Lakehouse architecture, Delta Lake, Spark-based processing, and Medallion Architecture (Bronze, Silver, Gold).
• Understanding of Databricks governance concepts, particularly Unity Catalog, data lineage, cataloging, metadata, access governance, data ownership, and data classification.
• Strong understanding of the data lifecycle including:
  • Data ingestion
  • Transformation
  • Storage
  • Data quality
  • Reconciliation
  • Data consumption
  • Analytics
  • Reporting
• Experience managing requirements and migration backlogs using Jira, Azure DevOps, Rally, or equivalent Agile delivery tools.
• Strong experience writing epics, features, user stories, acceptance criteria, business requirements, and functional requirements.
• Demonstrated ability to prioritize complex backlogs involving multiple business units, technology teams, and interdependent systems.
• Experience with Agile / Scrum / SAFe delivery models, including backlog refinement, sprint planning, PI/release planning, demos, and retrospectives.
• Strong understanding of data migration concepts including:
  • Source-to-target mapping
  • Data profiling
  • Data reconciliation
  • Historical-data migration
  • Migration waves
  • Parallel runs
  • Cutover planning
  • Production validation
  • Legacy decommissioning
• Working knowledge of data governance, data quality, metadata, lineage, privacy, security, regulatory controls, and stewardship.
• Strong stakeholder-management skills with the ability to communicate effectively with business leaders, engineering teams, architects, governance, security, risk, compliance, and executive stakeholders.
• Ability to translate complex technical concepts into clear business outcomes and translate business needs into actionable technical requirements.
• Strong analytical, problem-solving, prioritization, facilitation, and decision-making skills.
• Ability to work onshore in Atlanta with a minimum of 3 days per week in the office.

Travel: As required based on project and client needs; primary work location is Atlanta, Georgia.

Degree: Bachelor's degree in Computer Science, Information Systems, Data Engineering, Business, Engineering, or a related field, or equivalent work experience.

Nice to Have (But Not a Must)

• 10+ years of experience across Product Management, Data & Analytics, Business Analysis, or enterprise transformation programs.
• Experience as a Product Owner specifically for Databricks migrations, lakehouse modernization, or enterprise cloud data-platform programs.
• Experience migrating workloads from legacy platforms such as:
  • Hadoop / Hive
  • Teradata
  • Oracle
  • SQL Server
  • Informatica
  • Traditional data warehouses
  • On-premise data lakes
• Experience with enterprise governance/catalog platforms such as Collibra, Alation, Microsoft Purview, or equivalent.
• Experience working with cloud platforms including AWS, Azure, and/or GCP.
• Experience with BI and analytics platforms such as Power BI, Tableau, or equivalent.
• Understanding of APIs, data sharing, semantic layers, machine learning / AI consumption patterns, and downstream analytical applications.
• Experience working in regulated industries such as banking, financial services, insurance, healthcare, or other highly controlled environments.
• Certified Scrum Product Owner (CSPO), SAFe Product Owner/Product Manager (POPM), PMI-PBA, or equivalent Product / Agile certification.
• Databricks fundamentals or relevant Databricks certification.
• Experience working with globally distributed onshore/offshore engineering teams and third-party system integrators.

Key Skills

Education

Bachelor's degree