Manager, Data Program Management

HealthEquity•Remote,

3d•Remote

About The Position

The Manager, Data Program Management leads delivery of the enterprise Data & Analytics portfolio and scales execution through a small team of program/project managers and/or Product Owners. Reporting to the Chief Data Officer, this role is accountable for predictable delivery, stakeholder alignment, and governance of complex cross‑functional initiatives—especially in a regulated FinTech environment where controls, audit readiness, privacy, and risk management are essential. This leader ensures the CDO strategy translates into sequenced roadmaps, funded programs, integrated plans, managed dependencies, and measurable outcomes across core priorities including data quality, governance, and AI/ML enablement. The Manager Data Program Management reports to the Chief Data Officer.

Requirements

Bachelor’s degree in Business, Computer Science, Engineering, or related discipline or equivalent experience.
8+ years of program/portfolio management experience delivering complex cross functional initiatives.
3+ years of direct people management experience (performance management, coaching, hiring support).
Demonstrated experience delivering data, analytics, or platform programs in regulated or high risk environments.
Strong executive communication skills and ability to influence.
Experience in FinTech, Financial Services, or similarly regulated industries.
Familiarity with data governance, data quality, metadata/lineage, and controls-based operating models.
Experience enabling AI/ML delivery through data foundations (model ready datasets, feature stores, MRM/Responsible AI concepts).
Experience with cloud data ecosystems (e.g., modern data platforms, orchestration, BI/semantic layers).
Experience mentoring and enabling program/project managers and/or Product Owners to lead AI/ML initiatives effectively amid ambiguity, rapid iteration cycles, and complex dependencies.

Nice To Haves

PMP/PgMP/SAFe/Agile certifications preferred

Responsibilities

Manages and carries out the personnel actions for direct reports, including but not limited to hiring and scheduling; training and evaluating; coaching and managing performance; making salary, merit, or other compensation recommendations for team of direct reports; and making recommendations and/or taking corrective or disciplinary action as appropriate.
Own and drive execution of the enterprise data portfolio (multiple concurrent initiatives spanning platform, quality, governance, analytics, and AI/ML enablement).
Develop and maintain multi year roadmaps, annual plans, and quarterly execution commitments aligned to business strategy and capacity.
Establish clear program charters, scope, milestones, dependencies, and outcome measures; ensure delivery accountability across teams, including ensuring traceable documentation and audit ready evidence across Tier 1 initiatives (charters, requirements, approvals, decision logs, control evidence).
Identify delivery risk early; remove blockers, drive decisions, and ensure timely escalations with recommended options/tradeoffs.
Track and report program health (status, milestones, risks, dependencies, financials as applicable) to the CDO and executive stakeholders.
Embed governance and controls into delivery processes (privacy, security, retention, access controls, lineage, approvals, audit artifacts), partnering with Risk, Compliance, InfoSec, Legal, and Data Governance teams to ensure programs meet regulatory and internal control requirements.
Establish and continuously improve the data delivery operating model: intake, prioritization, planning, cadence, and reporting and improve portfolio transparency and predictability through capacity planning, dependency management, and clear governance forums.
Standardize program rituals and tooling (RAID logs, integrated plans, steering committees, decision logs, dashboards) and drive consistent delivery practices across agile, hybrid, and waterfall initiatives.
Lead program delivery and cross functional coordination of AI/ML enabling data initiatives, ensuring data readiness for model development, deployment, and scaling, partnering closely with Data Science, Data Engineering, Platform, Product, Risk, and Compliance to align AI/ML initiatives to enterprise and regulatory expectations.
Own execution of AI/ML foundational programs such as training data pipelines, curated model ready datasets, data labeling/annotation initiatives, feature store enablement, and model monitoring foundations (as applicable) and ensure AI/ML initiatives are appropriately sequenced within the broader data portfolio, balancing innovation, quality, and risk.
Establish and operationalize a repeatable AI/ML enablement playbook (intake → data readiness → delivery phases → controls/gates → launch readiness).
Serve as a strategic execution partner to the CDO; translate strategy into actionable plans and measurable outcomes and facilitating alignment across data, technology, and business leaders; drive decisions when priorities compete.
Occasional travel to attend training or meetings may be required