Senior Data Product Manager - Banking

Tiger Analytics; McLean (VA); On-site; USD 140,000 - 200,000; Full time

Job summary

Tiger Analytics is seeking an experienced Data Product Owner to bridge gaps between source-system teams, data engineering, and business stakeholders. You will help define data products, requirements, and acceptance criteria for enterprise data initiatives.

Lead data ingestion, governance, and modernization efforts across cloud platforms, ensuring timely delivery and high data quality for downstream consumers.

Qualifications

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

Responsibilities

• Partner with stakeholders to understand data products and required outcomes.
• Document source systems, data attributes, rules, and dependencies.
• Identify the types of business insights, KPIs, metrics, and downstream use cases.
• Develop understanding of data availability, SLA, latency, timeliness, and freshness.
• Collaborate with Data Engineers, Architects, DevOps, and QA on delivery.
• Translate requirements into clear, actionable tasks for data teams.
• Prioritize development tasks and remove blockers for data platforms.
• Facilitate communication between business and engineering teams.

Skills

Enterprise data projects

Data engineering teams

Source systems / SORs

Cloud data architecture

Data ingestion

ETL/ELT

Data quality

Data catalog

Data lineage

Data contracts

Agile/Scrum

CI/CD for data platforms

DevOps for data platforms

Stakeholder management

Requirements gathering

Analytical skills

Job description

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.

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.

• 10+ 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.

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.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.