Data Product Owner - Banking

Tiger Analytics • McLean, VA

3d

About The Position

Tiger Analytics is an advanced analytics consulting firm recognized for our deep expertise in Data Science, Machine Learning, and AI. Our partnerships with Fortune 100 companies enable us to tackle complex business challenges and drive value through innovative analytical solutions. We are looking for an experienced Data Product Owner who can bridge the gap between source system teams, data engineering, business stakeholders, and downstream data consumers. The ideal candidate will have strong experience working on enterprise data projects and a solid understanding of modern cloud data architectures, data products, data quality, data contracts, and engineering delivery practices.

Requirements

• 7+ years of experience working on enterprise data, analytics, data product, or technology projects.
• Strong experience working with data engineering teams and enterprise data platforms.
• Experience working with source systems/SORs and understanding data attributes, business rules, constraints, and downstream use cases.
• Strong understanding of modern cloud data architecture and data lifecycle.
• Hands-on understanding of: Data ingestion, ETL/ELT, Bronze/Silver/Gold architecture, Data quality, Data catalog, Data lineage, Data contracts, Data testing
• Experience working with Agile/Scrum engineering teams.
• Understanding of CI/CD, DevOps, release management, and testing practices for data platforms.
• Strong requirements gathering, documentation, prioritization, and stakeholder management skills.
• Ability to work effectively between business stakeholders and technical engineering teams.
• Strong analytical and problem-solving skills.

Responsibilities

• Partner with source-system owners, SMEs, and technology teams to understand modern cloud-based Systems of Record (SORs) and the data they produce.
• Understand and document source systems, data attributes, business definitions, relationships, rules, constraints, and dependencies.
• Identify the types of business insights, KPIs, metrics, and downstream use cases that can be supported by the underlying data.
• Develop a strong understanding of data availability, SLA, latency, timeliness, and freshness requirements for downstream data products.
• Understand source-system integration options, connectivity requirements, access mechanisms, and associated security considerations.
• Translate source-system knowledge into clear and actionable requirements for data engineering teams.
• Work closely with Data Engineers, Architects, Developers, QA, and other technical teams on a day-to-day basis.
• Validate technical assumptions and clarify requirements, dependencies, priorities, and acceptance criteria.
• Prioritize data product development tasks and help engineering teams remove blockers.
• Facilitate communication between engineering teams and source-system SMEs for connectivity, access, sample data, data availability, and technical dependencies.
• Define and enable appropriate data testing and validation strategies.
• Support engineering teams throughout development, testing, deployment, and production release.

Benefits

• Significant career development opportunities exist as the company grows.
• The position offers a unique opportunity to be part of a small, fast-growing, challenging, and entrepreneurial environment, with a high degree of individual responsibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed