Technical Product Owner II

📋 Description

• • Serve as the execution link between product strategy and data engineering delivery, translating business requirements into well-defined Epics and User Stories to guide Agile teams from refinement to release.
• • Partner with the Product Manager and cross-functional stakeholders to define, maintain, and prioritize business requirements, use cases, and acceptance criteria for the centralized data platform.
• • Develop and maintain a deep working understanding of the data platform architecture, including ingestion patterns, data models, and governance frameworks to accurately scope work and ask informed technical questions.
• • Lead sprint planning and backlog refinement sessions with engineers, analysts, and QA to ensure clear scope, realistic effort estimation, and alignment on deliverables.
• • Write and execute SQL queries and data transformation scripts to validate data outputs, explore datasets, and support functional and data quality acceptance testing.
• • Define clear, testable acceptance criteria for QA teams to validate both functional behavior and data integrity across ingestion and modeling pipelines.
• • Help define, document, and enforce data quality standards, governance policies, and data taxonomy across the centralized data platform, collaborating with engineering and analytics teams to remediate issues.
• • Collaborate with Design teams to shape user flows for internal tools and client-facing data product interfaces.
• • Produce and maintain comprehensive business and technical documentation for stakeholders across product, engineering, and go-to-market functions.
• • Stay current on industry trends in modern data stack architectures—including data lakehouse, data mesh, and ELT pipelines—and bring market context into roadmap and prioritization discussions.
• • Ensure all delivered solutions meet both business objectives and technical standards throughout the software development lifecycle.
• • Leverage AI-assisted tools and innovative workflows to enhance personal and team productivity in backlog management, documentation, and data validation tasks.
• • Work with cloud data warehouse platforms (e.g., Snowflake) to understand and validate data workflows, transformations, and storage models.
• • Apply practical knowledge of data governance concepts including data lineage, metadata management, and data catalog tooling to improve platform reliability and compliance.
• • Translate complex technical concepts for business audiences and business needs for engineering teams with clarity and precision.
• • Manage a high-visibility product backlog for a platform that powers client-facing data products such as dataset delivery feeds, analytics, reporting solutions, and audience intelligence tools for financial institutions.
• • Ensure alignment between engineering deliverables and data quality requirements, platform standards, and governance policies across the organization's core banking, payments, digital banking, and CRM data sources.
• • Use Agile practices to drive iterative delivery of data-as-a-product offerings that serve both internal and external clients.
• • Engage with emerging AI-driven data tooling to evaluate and adopt productivity-enhancing workflows in product ownership practices.