Enterprise Data Product Lead - Cloud Data & Quality

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 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.