Senior Data Product Manager - Banking

Tiger Analytics Inc.; McLean (VA); On-site; USD 130,000 - 185,000; Full time

Job summary

Tiger Analytics Inc. is seeking an experienced Data Product Owner to bridge gaps between source-system teams, data engineering, and business stakeholders. You will shape data products, define requirements, and guide delivery across modern cloud data architectures.

Ideal candidates have 10+ years on enterprise data projects, strong collaboration with data engineering teams, and expertise in data quality, contracts, and lifecycle management. This role offers growth in a fast-growing analytics firm.

Qualifications

• 10+ years of experience on enterprise data/analytics projects.
• Experience with data engineering teams and enterprise data platforms.
• Understanding of source systems/SORs and downstream use cases.
• Strong knowledge of cloud data architectures and data lifecycle.

Responsibilities

• Partner with source-system owners and tech teams to understand cloud-based Systems of Record data.
• Document data attributes, business rules, constraints, and dependencies.
• Identify KPIs, metrics, and downstream use cases for data products.
• Define data availability, latency, and testing strategies for downstream data products.
• Translate requirements for data engineering teams and support delivery lifecycle.
• Prioritize data product work and assist teams in removing blockers.
• Communicate with stakeholders and SMEs on connectivity, access, and data dependencies.
• Support development, testing, deployment, and production releases.

Skills

Enterprise data projects

Data engineering teams

Cloud data architecture

Stakeholder management

Agile/Scrum

CI/CD/DevOps

Data quality

Data contracts

Data lineage

Data ingestion

Tools

CI/CD tools

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.