Senior Data Product Manager - Banking

Tiger Analytics; Illinois; On-site; USD 120,000 - 180,000; Full time

Job summary

Tiger Analytics is seeking an experienced Data Product Owner who can bridge source system teams, data engineering, business stakeholders, and downstream data consumers. The ideal candidate will have strong experience on enterprise data projects and a solid understanding of cloud data architectures, data products, data quality, data contracts, and engineering delivery practices.

Significant career development opportunities exist as the company grows.

Qualifications

• 10+ years of enterprise data experience.
• 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.
• 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 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 and tech teams to understand cloud-based Systems of Record and data they produce.
• Document source systems, data attributes, business definitions, relationships, rules, constraints, and dependencies.
• Identify insights, KPIs, metrics and downstream use cases for the data.
• Understand data availability, SLA, latency, timeliness, and freshness for downstream data products.
• Understand integration options, connectivity, access mechanisms, and security considerations.
• Translate knowledge into clear requirements for data engineering teams.
• Collaborate daily with data engineers, architects, developers, QA and other teams.
• Validate assumptions and clarify requirements, dependencies, priorities, and acceptance criteria.
• Prioritize data product tasks and help remove blockers.
• Facilitate communication between engineering teams and source-system SMEs on connectivity and data availability.
• Define and enable data testing and validation strategies.
• Support teams through development, testing, deployment and production release.

Skills

Data Product Owner

Enterprise data

Data engineering collaboration

Cloud data architecture

Data quality

Data contracts

Agile/Scrum

CI/CD

DevOps

Stakeholder management

Requirements gathering

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.