Serve as a subject matter expert (SME) for enterprise customer data concepts including customer identity, householding, customer hierarchies, contact data, consent/preferences, and customer attributes.
Drive customer data definition alignment (business glossary, critical data elements, metadata), ensuring consistent meaning and usage across platforms and lines of business.
Contribute to customer data strategy and roadmap, identifying opportunities to modernize customer data capabilities and reduce fragmentation.
Execute customer data quality management practices: profiling, monitoring, rule definition, threshold tuning, and performance reporting.
Lead investigation of data anomalies and recurring defects using structured root cause analysis; coordinate remediation with upstream/downstream partners.
Implement scalable controls and preventive measures (e.g., validation rules, reconciliation checks, exception handling, automation) to reduce repeat issues.
Partner with analytics and data science teams to translate business problems into data requirements, analytically ready datasets, and reusable features (e.g., customer identity, household, relationship, and behavioral attributes).
Support model development and monitoring by improving data completeness, stability, and explainability; document assumptions, transformations, and known limitations for appropriate use.
Enable business decisioning use cases by defining customer data inputs for segmentation, targeting, credit/marketing decisioning, personalization, and next-best-action solutions.
Establish fit-for-purpose data quality checks for analytic pipelines (distribution shifts, outliers, freshness, leakage risks) and coordinate remediation when thresholds are breached.
Collaborate with partners to develop KPIs and measurement approaches that connect data improvements to business outcomes (e.g., conversion, retention, risk performance, operational efficiency).
Support customer data governance routines including stewardship forums, issue/decision logs, and control evidence management to enable consistent, trusted use of customer data across reporting, analytics, and decisioning.
Ensure customer data processes and controls align to risk, audit, privacy, retention, and regulatory requirements while supporting responsible innovation and scalable analytic consumption.
Produce leadership-ready reporting on customer data risk posture, control health, remediation progress, and key metrics; highlight impacts to critical reporting, models, and decision solutions.
Partner with data engineering and product teams to define requirements for customer data solutions (MDM/EDS/APIs/data lake), including onboarding, lineage, analytic consumption patterns, and performance/availability needs.
Support design and operationalization of “trusted” customer data products and feature sets (e.g., curated views, golden records, identity/household features), including documentation, data contracts, and consumption guidance.
Enable analytics, operations, and customer-facing teams by improving accessibility to reliable customer datasets and features, advising on proper usage, and accelerating time-to-insight/time-to-decision.
Act as a connector across business, operations, risk, and technology—translating business needs into data requirements and actionable delivery plans.
Mentor analysts/junior data stewards and promote standards, playbooks, and repeatable practices.
Influence without authority through clear narratives, fact-based recommendations, and proactive stakeholder engagement.
Requirements
Experience with Master Data Management (MDM), customer identity resolution, probabilistic matching, or householding solutions.
Familiarity with data governance frameworks and tools (e.g., Collibra/Alation, Archer/GRC tools, data cataloging/lineage platforms).
Experience supporting regulatory programs, MRAs, audit readiness, and control evidence practices.
Experience supporting analytics and data science workflows (feature engineering, cohort/segment analysis, model inputs/outputs) and translating business decision needs into data solutions.
Familiarity with decisioning and measurement practices (e.g., segmentation strategies, champion/challenger testing, experimentation, KPI design) and working with stakeholders to evaluate impact.
SQL proficiency and experience working in data lake / warehouse environments (cloud and/or on-prem).
Background in financial services data management or other highly regulated environments.
Tech Stack
Cloud
SQL
Benefits
medical/prescription drug coverage (with a Health Savings Account feature)
dental and vision options
employee and spouse/child life insurance
short and long-term disability protection
401(k) with PNC match, pension and stock purchase plans
dependent care reimbursement account
back-up child/elder care
adoption, surrogacy, and doula reimbursement
educational assistance, including select programs fully paid
a robust wellness program with financial incentives
maternity and/or parental leave
up to 11 paid holidays each year
9 occasional absence days each year, unless otherwise required by law
between 15 to 25 vacation days each year, depending on career level; and years of service