at AAA Mid Atlantic in Wilmington, Delaware, United States Job Description Wilmington, DE (Job Posting) Cincinnati, OH - Central Parkway (Job Posting) Full time 44509 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

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+ 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 DevSecOps 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 testing; ensure traceability from requirements and source-to-target rules through test evidence and release approval.

+ Coordinate UAT with business owners and BI consumers, including representative test data, expected results, defect triage, sign-off, release readiness, and validation that downstream reporting and analytics are materially complete before production deployment.

+ Own the post-production data quality control framework, including preventive and detective controls, file and schema validation, record-count and financial reconciliation, business-rule thresholds, anomaly detection, exception workflows, issue ownership, root-cause analysis, remediation, certification, and control evidence.

+ Create and maintain production monitoring, alerting, observability, runbooks, support procedures, service measures, and operational dashboards covering availability, freshness, completeness, accuracy, pipeline reliability, latency, recoverability, and cost; ensure recurring incidents and temporary fixes are converted into backlog items and permanent improvements.

+ Own financial management for the data warehouse environment, including annual operating and capital plans, project forecasts, vendor and license spend, cloud consumption, labor mix, chargeback/showback inputs, business-case development, variance management, and investment optimization.

+ Drive cloud infrastructure and FinOps optimization across compute, storage, query processing, orchestration, data movement, reservations/commitments, retention, and BI capacity; establish cost transparency, budgets, alerts, unit-cost measures, rightsizing, workload tuning, and architecture trade-off reviews.

+ Provide accountable project and program delivery for enterprise data initiatives, including scope, schedule, budget, staffing, dependencies, risks, issues, quality, vendor performance, executive reporting, change control, adoption, and benefits realization.

+ Balance strategic delivery, maintenance, production support, governance, and platform modernization through capacity planning and resource allocation; proactively identify skill, staffing, partner, and knowledge-retention risks.

+ Lead enterprise data governance execution, including business glossary, data ownership and stewardship, critical data elements, metadata, lineage, access, privacy, retention, master/reference data, quality standards, certification, and controlled change management.

+ Manage BI platform administration and future direction in coordination with BI leadership, including semantic-model standards, certified datasets, workspace and capacity governance, self-service enablement, security, lifecycle management, and alignment with the enterprise data architecture.

+ Establish architecture, engineering, quality, and delivery review forums; define measurable standards and quality gates; and ensure exceptions, risks, and technical decisions are documented, approved, and actively managed.

+ Coach and develop team members; set clear technical and delivery expectations; build succession and skill-development plans; and promote strong business-domain knowledge, engineering discipline, documentation, collaboration, and accountability.

+ Other duties as as To view full details and how to apply, please login or create a Job Seeker account