Lead complex data product initiatives, including cross‑functional efforts with broad organizational impact, and serve as a key contributor to large‑scale planning that advances enterprise data enablement and platform capabilities.
Directly interrogate customer data using a variety of technical approaches (e.g., SQL and related technologies) to support product decisions and regulatory initiatives.
Apply strong technical skills and customer data domain knowledge to perform in‑depth data analysis, identify data quality issues and gaps, and define target logic supporting customer data modernization.
Review and analyze complex, multi‑faceted data product initiatives that may span longer time horizons or involve ambiguous or unprecedented factors, while ensuring alignment with established data governance, standards, and controls.
Make informed decisions in complex scenarios by leveraging a solid understanding of data, analytics, and integration needs of line‑of‑business partners to influence prioritization, roadmaps, and architectural direction.
Collaborate strategically with peers, colleagues, and mid‑level to senior leaders across product, data management, engineering, and architecture teams to design high‑quality, scalable data products and analytics solutions.
Provide strategic input into new use‑case intake, prioritization, and product roadmap definition, ensuring alignment to business value and enterprise data strategy.
Manage and curate complex datasets with a continuous focus on downstream consumers and business use cases, while adhering to data governance and quality standards.
Create and maintain product roadmaps across the full product lifecycle, including detailed specifications, requirements, and data flows for data capabilities.
Serve as a strategic liaison between data management, product, data engineering, and architecture teams throughout the product lifecycle.

Requirements

5+ years of data product or data management experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
3+ years of hands‑on data analysis experience, including querying and analyzing large datasets using technologies such as SQL, Spark, and/or Python.
Experience within financial services, particularly in highly regulated enterprise environments.
Strong customer data domain knowledge, with prior experience working with customer, party, or identity‑related data considered a significant plus.
Demonstrated ability to bridge business needs and technical implementation through data‑driven analysis and clear communication.
Experience using AI tools to refine Features and backlogs.

Benefits

Health benefits
401(k) Plan
Paid time off
Disability benefits
Life insurance, critical illness insurance, and accident insurance
Parental leave
Critical caregiving leave
Discounts and savings
Commuter benefits
Tuition reimbursement
Scholarships for dependent children
Adoption reimbursement

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data analysisdata product managementdata governancedata qualitySQLSparkPythondata integrationdata modernizationdata lifecycle management

Soft Skills

strategic collaborationcommunicationdecision makinginfluenceprioritizationproblem solvingcustomer focusanalytical thinkingcross-functional leadershipadaptability