Technical Product Manager, Specialist

Core Responsibilities

• Own technical product management for master data products, with end - to - end accountability across the data lifecycle: ingestion, transformation, modeling, orchestration, storage, and consumption . Actively contribute s to solution design and continuous technical improvement.

• Lead cross functional collaboration with data engineering, BI/analytics engineering, infrastructure , governance, and business teams to define and operationalize best practices for master data management (MDM), reference data management (RDM), data modeling, data quality frameworks, and data contracts .

• Apply hands on SQL proficiency to explore datasets, validate requirements, assess data quality, and independently analyze issues and trends that inform prioritization, roadmap decisions, and stakeholder conversations.

• Translate business needs into executable data product requirements , including hierarchies, schemas, transformations, data quality rules, SLAs, and downstream consumption patterns .

• Coach and guide delivery teams on data product best practices-backlog structure, dependency management, technical tradeoff analysis, and outcome

• based planning-while ensuring clear, consistent communication for data producers and consumers.

• Partner with engineering and stakeholders to resolve production issues , including data quality defects, pipeline failures, orchestration errors, and downstream analytics breakages. Drive query level investigation , root cause analysis, and sustainable remediation.

• Support the launch and adoption of master and reference data products by improving usability, trust, and consistency across operational systems, analytics, and reporting use cases.

• Use quantitative analysis and data profiling to continuously improve data accuracy, completeness, consistency, and timeliness, balancing governance requirements with usability and speed.

• Influence roadmap and prioritization decisions by representing data quality risk, architectural dependencies, and platform constraints in business planning discussions.

• Participate in engineering delivery practices , including backlog refinement, sprint planning, design reviews, CI/CD for data pipelines, job orchestration controls , and observability for data quality and freshness.

• Contribute to initiatives spanning metadata capture, data discoverability, governance workflows, and domain aligned ownership models , and support special projects as needed.

• Undergraduate degree or equivalent combination of training and experience required . Minimum of five years related work experience. Advanced degree in information technology or hands-on experience with data engineering, business intelligence / analytics engineering preferred.

• Two years leading large cross-functional teams on major organizational projects preferred.