•Define critical lending data concepts by establishing clear business definitions, metadata, and usage context that enable consistent interpretation across teams.
•Classify and protect data by applying appropriate sensitivity and handling expectations and ensuring data is safeguarded across creation, provisioning, and consumption.
•Document end-to-end data flows by partnering with technology and analytics teams to maintain lineage and dependency visibility across applications and analytical use cases.
•Establish data quality expectations by setting measurable rules, thresholds, and monitoring approaches aligned to business outcomes and reporting needs.
•Investigate data issues by performing root-cause analysis, quantifying business impact, and driving sustainable remediation with accountable owners and timelines.
•Partner with engineering and architecture teams to enable reliable data sourcing and delivery patterns that support product development and analytical consumption.
•Translate business needs into clear data requirements, including definitions, critical elements, quality expectations, and downstream consumption requirements.
•Drive cross-functional execution by managing priorities, aligning stakeholders, and removing blockers to deliver committed data outcomes.
•Operationalize governed automation by using approved assisted-analysis capabilities to accelerate documentation, profiling, and issue investigation while maintaining appropriate oversight and controls.
Required qualifications, capabilities, and skills
•Bachelor’s degree in a related field or equivalent professional experience in data management, data governance, or a related discipline.
•8+ years of industry experience with demonstrated work in data management, data governance, data risk, data architecture, data engineering, analytics, or related disciplines.
•Demonstrated understanding of data lifecycle concepts, including metadata, classification, sourcing, lineage, quality, protection, retention, storage, and consumption.
•Demonstrated ability to analyze complex data flows and dependencies across source systems, transformations, provisioning, and downstream consumption.
•Experience defining and documenting data requirements, including data definitions, metadata, critical data elements, quality expectations, and consumption requirements.
•Experience investigating data quality issues, performing root-cause analysis, assessing business impact, and recommending sustainable remediation.
•Working knowledge of modern data platforms, data architecture, and data integration concepts, with the ability to partner effectively with engineering and architecture teams.
•Experience using data analysis techniques to profile, validate, reconcile, and investigate datasets.
•Experience using assisted-analysis tools to accelerate data analysis, documentation, requirements development, and issue investigation in a controlled environment.
•Demonstrated ability to communicate complex data topics clearly to business, technology, analytics, risk, and control stakeholders.
•Proven ability to drive deliverables independently through cross-functional partnerships while managing competing priorities.
