Manager I, Data Analytics (Lending Analytics Data Stewardship)

Navy Federal • Pensacola, FL

1d

About The Position

Navy Federal Credit Union currently does not provide sponsorship for this role. Applicants must be authorized to work in the United States without the need for current or future sponsorship. Oversees the collection, cleaning, validating, and analyzing complex data sets and supports Lending Analytics-owned data ecosystems to support business decisions. Translates data governance and analytics plans into operational deliverables while optimizing processes for data reliability and scalability. Serves as a thought leader in innovating and automating data quality monitoring (e.g., anomaly detection) and enhancing data assets and products through analytical data engineering. Develops and maintains the Lending Analytics Data Ecosystem knowledge base to enable broad adoption of trusted data products through documentation, enablement, and stakeholder partnership. The role requires credit union wide partnerships to conduct comprehensive data quality assessments for existing and newly introduced data sets, and to lead structured remediation feedback loops when issues arise. This position is eligible for the TalentQuest employee referral program. If an employee referred you for this job, please apply using the system-generated link that was sent to you.

Requirements

• Bachelor’s degree in related field or equivalent combination of training, education and experience
• College/university degree and 5+ years work experience; 1+ years of management experience
• Proven ability to lead a team of data analysts, setting clear objectives and enabling team members to contribute effectively to analytics projects
• Ability to identify opportunities for improvement within data analytics processes and implementing best practices for efficiency
• Effective in communicating analytical results and recommendations to non-technical stakeholders, bridging the gap between data and business implications
• In-depth knowledge of data analytics tools and programming languages (e.g., SQL, Python, R) to guide analytical methods and practices
• Experience designing and operating data quality frameworks (rules/thresholds, monitoring, issue management, and Service Level Agreements/SLAs) and partnering with governance/risk stakeholders
• Hands-on ability with data observability/automation patterns (anomaly detection, automated controls, alerting, and scalable triage workflows)
• Strong analytical data engineering capability (SQL + Python; building curated datasets, reusable features, and metric layers)
• Experience creating and maintaining data documentation/knowledge assets (data dictionaries, definitions, lineage/context, and user enablement materials)
• Proven ability to influence without authority and drive adoption of standards and data products across cross-functional stakeholders
• Effective leadership in managing a team, driving performance to meet organizational goals
• Ability to identify challenges and develop practical solutions that optimize team performance
• Skill in managing daily operations with a focus on efficiency and productivity
• Strong interpersonal skills for coordinating with team members and other departments
• Commitment to empowering team members to take initiative and make decisions in their roles
• Proficiency in setting goals and evaluating team performance to achieve business objectives

Nice To Haves

• Familiarity with metadata management / data cataloging tools and governance concepts (ownership, stewardship, access, controls).
• Master’s Degree in related field or equivalent combination of training, education and experience.

Responsibilities

• Manages a team of Data Analysts performing data collection, profiling, and cleaning
• Develop work plans and manage the execution of daily, weekly, and monthly reporting and analytics activities
• Lead execution of data collection/extraction projects that support data governance and recommend leading practices in data collection decisions and practices
• Lead innovation and automation of data quality monitoring, including anomaly detection, trend-based alerting, and scalable exception management workflows
• Collaborate with business units and data scientists to define data quality rules and implement standard processes
• Ensure accuracy, integrity, and usability of cleaned data used across dashboards and ad-hoc reports
• Enhance Lending Analytics data assets and products through analytical data engineering, including feature creation, metric standardization, and curated datasets that accelerate downstream analytics
• Develop and own the Lending Analytics Data Ecosystem knowledge base (data catalog content, data dictionaries sources, lineage/context, definitions, and usage guidance) to improve discoverability and correct use of data products
• Evangelize data products and standards by partnering across Lending Analytics, enterprise technology and data teams, and business stakeholders; deliver enablement (office hours/training) and drive adoption of trusted datasets
• Track team performance, assign projects, and evaluate capacity against business needs
• Coach team on advanced validation and profiling techniques to reduce inconsistencies and redundancies

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Number of Employees: 5,001-10,000 employees