Product Owner II, Analytics (Dublin, CA)

SavvyMoney•Dublin, CA

53d•$130,000 - $145,000•Hybrid

About The Position

About SavvyMoney: SavvyMoney is a leading San Francisco East Bay fintech company. We provide integrated credit score and personal finance solutions to over 1,500 + bank and credit union partners nationally. The SavvyMoney solutions integrate with more than 43 digital banking platforms. Recognized by the San Francisco Business Times and the Silicon Valley Journal as one of the "Top 20 Places to Work in the San Francisco Bay Area" for the last 3 years, and also listed as an Inc.5000 Fastest Growing Company for the last 3 years. We pride ourselves on a culture of collaboration, innovation, and mutual respect. We're a team that supports each other's growth, celebrates successes, and genuinely enjoys the work we do. Our corporate offices are in Dublin, CA and we offer a hybrid work environment with some days at the corporate office and some days working from home. We are also open to remote candidates who can periodically travel to the office for in-person meetings. We are seeking a Data and Analytics Product Owner to help drive the evolution of our SaaS-based analytics platform that delivers actionable insights to our financial institution (FI) partners and internal stakeholders. This role is ideal for someone with strong data engineering, SQL, and analytics product management experience who can bridge business needs with data-driven solutions. A background or interest in AI/ML applications in analytics is a strong plus. You will report to the Senior BI-Analytics Product Manager and work closely with the data engineering and business teams to enhance analytics capabilities, ensure data quality and reliability, and support new analytics and AI-driven features.

Requirements

Bachelor’s degree in Computer Science, Data Analytics, Engineering, or a related field.
4–5 years of experience as a Product Owner, Data Product Manager, or Analytics Product Lead, preferably in a SaaS or fintech environment.
Strong SQL skills and familiarity with data modeling, ETL pipelines, and analytics architectures.
Proven experience working closely with data engineering and BI/analytics platforms including AWS products and Tableau or equivalent.
Working understanding of AI/ML concepts and how they can be applied in analytics products.
Expertise with Agile methodologies and tools like Jira and Confluence.
Excellent communication, problem-solving, and stakeholder management skills.
Experience in consumer credit or financial data analytics is a plus.

Nice To Haves

Experience with digital banking platforms and loan origination systems.
Proficiency with marketing, design & project management tools (Salesforce, Jira, Canva, Figma, Creative Suite, Highspot, Seismic, Confluence, PowerPoint/Google Slides).
Bachelor's degree in Marketing, Business, or a related field.
Facility with AI tools (Gemini, ChatGPT, Perplexity)

Responsibilities

Collaborate with Product Managers, data engineering, and business stakeholders to define detailed product requirements for analytics features and data pipelines.
Translate high-level business needs into clear epics, stories, and acceptance criteria, capturing data dependencies and edge cases.
Help define data models, metrics, and event-tracking needs for both internal and partner-facing analytics.
Own and prioritize the analytics product backlog, ensuring alignment with business strategy and data roadmap.
Manage sprint planning, backlog grooming, and sprint ceremonies in partnership with engineering and the BI team.
Oversee bug triage, QA validation, and release readiness for analytics features.
Support go-to-market team for planning and coordinating launch timelines, internal enablement, and stakeholder communication.
Partner with data engineers to model and transform event-level data into unified, scalable data sets.
Leverage SQL and data visualization to validate analytics outputs, monitor product performance, and identify areas for improvement.
Ensure high standards for data accuracy, consistency, and lineage and the analytics data lake.
Collaborate on the implementation of AI/ML models that enhance predictive insights and reporting automation.
Act as a bridge between technical and business teams, ensuring shared understanding of requirements, delivery timelines, and priorities.
Communicate sprint progress, product updates, and analytics insights to stakeholders across Product, Marketing, and Partner Success teams.
Maintain comprehensive product and data documentation, including KPIs, metrics definitions, and release notes.
Support compliance and governance standards for FI and consumer data security.