Manager, Enterprise Data

AAA Club Alliance is hiring for an Enterprise Data Manager to join our team!

What We Offer You:

As part of our team, you’ll enjoy a total rewards package designed to support your well-being, growth, and work-life balance. Our package includes:

Competitive annual salary; the starting base compensation for this position is: $105,147-$167,018
* Annual Bonus Eligibility Hybrid schedule (3 days on-site weekly)
Comprehensive health benefits package

Generous accrued paid time off + 8 paid holidays
401(K) plan with company match up to 7%
Professional development opportunities and tuition reimbursement

Paid time off to volunteer & company-sponsored volunteer events throughout the year Other benefits include a complimentary AAA Membership, Health & Wellness Program, Health Concierge Service, Life Insurance and Short Term/Long Term Disability
* The base pay range shown is a guideline for compensation and ultimate salary offered will be based on factors such as applicant experience and geographic location.

Primary Responsibilities:

Lead all aspects of the Enterprise Data team, including employees, consultants, managed-service partners, and cross-functional contributors across business analysis, data analysis, architecture, modeling, engineering, quality assurance, BI enablement, platform operations, and production support. Own the enterprise data warehouse as a technology product and business capability, with accountability for service reliability, delivery performance, stakeholder outcomes, platform health, technical debt, security, cost, and continuous improvement.

Define, maintain, and execute the long-term enterprise data warehouse strategy and multi-year roadmap, including target-state architecture, platform modernization, cloud migration, technical debt reduction, data-product evolution, semantic-layer development, resiliency, and lifecycle management.

Own the consolidated backlog for strategic initiatives, regulatory and control needs, production defects, maintenance, technical debt, platform upgrades, and business enhancements; establish transparent intake, sizing, prioritization, dependency management, release planning, and roadmap communications.

Partner with business leaders, product owners, BI teams, and subject-matter experts to gather and validate business processes, decisions, metrics, events, entities, grain, history, security, service-level, and nonfunctional requirements, translating them into testable epics, features, stories, acceptance criteria, and data contracts.

Lead source-data discovery, profiling, and analysis across databases, APIs, files, streams, and third-party data; ensure teams document source meaning, record behavior, change patterns, authoritative ownership, data quality, lineage, retention, and fitness for use.

Establish and govern enterprise data architecture across ingestion, landing, lake/lakehouse, integrated warehouse, operational data, master and reference data, semantic, presentation, analytics, AI, metadata, security, observability, and consumption layers.

Lead conceptual, logical, physical, dimensional, relational, and semantic data modeling; ensure consistent business definitions, conformed dimensions, appropriate grain and history, reusable structures, lineage, auditability, performance, and alignment to enterprise architecture standards.

Provide technical leadership for ETL/ELT and data integration design and development, including ingestion, cleansing, transformation, source-to-target mapping, business-rule implementation, reconciliation, metadata capture, error handling, restartability, performance tuning, and maintainable code patterns.

Own overall integration job orchestration and dependency design across batch, event-driven, API, streaming, and near-real-time workloads; require dependency-based triggers, controlled parallelism, recovery procedures, failure isolation, alerting, and end-to-end schedule optimization rather than fragile time-based scheduling.

Establish software-engineering and Dev Sec Ops  standards for data solutions, including version control, peer review, branching, automated unit and data tests, artifact management, infrastructure as code, environment configuration, secrets management, CI/CD pipelines, segregation of duties, release approvals, rollback, and production deployment.

Define and enforce an end-to-end test strategy covering unit, component, schema, transformation, integration, regression, performance, security, reconciliation, disaster-recovery, and user-acceptance…