Manager, AI & Data Engineering

Why Join Apple?

At Apple Federal Credit Union, we're more than a financial institution; we're a community-focused organization powered by passionate people. With 24 branches across Northern Virginia and a proud legacy of service, we're committed to improving the lives of our members and the communities we serve.

We believe our employees are our greatest asset. That's why we foster a supportive workplace culture that values inclusiveness, innovation and growth. Whether you're just starting out or advancing your career, you'll find opportunities for professional development, mentorship and meaningful impact.

Why Work at Apple FCU

• Recognized as a USA Top Workplace (2025) and Top Workplace by The Washington Post (2025)
• Collaborative, welcoming environment with forward-thinking leadership
• Competitive, comprehensive benefits package, including:
  • Medical, dental and vision coverage
  • 401(k) with employer match
  • Paid time off and 11 paid federal holidays
  • Paid volunteer time to give back
  • Tuition reimbursement and ongoing training opportunities
  • Annual TEAM Bonus plan.

Role:

Under the general supervision of the Director, Data Analytics & Enterprise Architecture, and in adherence to established policies and procedures, the Manager, AI & Data Engineering will lead Apple FCU's data engineering capabilities and drive the adoption of AI engineering practices that transform how staff consume enterprise data. This role is accountable for building and operating a high-performing engineering team that delivers reliable, governed, and scalable data products and enables AI-powered, natural-language access to trusted insights.

This position owns the engineering operating model and delivery execution, including work intake, prioritization, capacity planning, delivery predictability, and operational maturity. The Manager establishes and enforces engineering standards (documentation, testing discipline, repeatable deployments, runbooks, and data quality validation) and coordinates delivery across technical teams and stakeholders to ensure work is scoped, sequenced, and aligned to business outcomes.

A core responsibility is treating AI as an engineered capability, not an experiment, by setting pragmatic tooling and platform direction, establishing "golden path" delivery patterns, and ensuring production-grade supportability (architecture, Azure/Fabric alignment, compute/runtime considerations, observability, and cost-awareness). The role partners with leadership to balance innovation with governance, security, and reliability.

The candidate will be expected to perform their duties with a mindset that reflects The Apple Way principles:
Team Up, Serve with Purpose, Challenge Yourself, and Own It. A keen awareness of and compliance with credit union policies and procedures, as well as regulations pertaining to the Bank Secrecy Act, is imperative. Additionally, the Manager, AI & Data Engineering will undertake other information technology responsibilities as delegated by the Director, Data Analytics & Enterprise Architecture.

Essential Functions & Responsibilities:

Team Leadership, Management & Capability Building:

• Lead, coach, and develop the Data Engineering function, fostering a collaborative, high-performing engineering culture aligned to The Apple Way (Team Up, Serve with Purpose, Challenge Yourself, Own It).
• Recruit, interview, and onboard engineering talent as needed; maintain balanced capability across ingestion, transformation, platform operations, and AI-enabled engineering practices.
• Establish clear expectations for engineering craftsmanship and accountability (quality, documentation, testing discipline, code review norms, operational readiness).
• Provide routine performance feedback and formal reviews; create development plans and growth pathways for team members and ensure continuity of knowledge across the function.

Delivery Management (Workflow, Intake, Capacity, Predictability)

• Own and operate the team's work intake, prioritization, and capacity planning processes (backlog health, sprint/iteration planning, WIP management, dependency visibility, and delivery predictability).
• Coordinate delivery across Data Engineering, Data Analytics, and business stakeholders to ensure work is appropriately scoped, sequenced, and aligned to business outcomes.
• Provide routine reporting and communication of delivery status, risks, tradeoffs, and outcomes; ensure stakeholders have consistent visibility into priorities and timelines.
• Identify and remove blockers (technical, process, resourcing, cross-team dependencies) and drive continuous improvement to increase throughput and reduce cycle time without sacrificing quality.
• Maintain a "production-minded" operating rhythm: clear definition of done, handoff readiness, and supportability expectations for delivered work.

Data Platform Reliability, Operational Maturity & Quality

• Oversee data platform reliability and operational maturity: monitoring patterns, incident triage practices, root-cause remediation, and…