Manager, Enterprise Data

AAA Club Alliance•Wilmington, DE

2d•Hybrid

About The Position

AAA Club Alliance is hiring an Enterprise Data Manager to lead its Enterprise Data team and own the enterprise data warehouse as both a technology product and a business capability. The role is accountable for platform reliability, delivery performance, stakeholder outcomes, platform health, technical debt, security, cost, and continuous improvement. It leads employees, consultants, managed-service partners, and cross-functional contributors in areas including data architecture, modeling, engineering, quality assurance, BI enablement, platform operations, and production support. The manager defines and executes the long-term data warehouse strategy and multi-year roadmap, including target architecture, modernization, cloud migration, data products, semantic layers, resiliency, and lifecycle management. The position owns intake and prioritization of work, project and program delivery, financial planning, vendor management, capacity planning, and communication with business and technical stakeholders. The role establishes enterprise data architecture and engineering standards across ingestion, warehouse and lakehouse, operational data, master and reference data, semantic, analytics, AI, metadata, security, observability, and consumption. It oversees data modeling, ETL/ELT and integration, orchestration, software engineering and DevSecOps, testing and UAT, data-quality controls, production monitoring, governance, and BI platform administration. It also coaches and develops team members and promotes technical discipline, documentation, collaboration, and accountability.

Requirements

Bachelor's degree in Computer Science, Information Technology, Data Engineering, Information Systems, Business, or a related field; an equivalent combination of education and relevant experience may be considered.
8+ years of progressive experience in enterprise data warehousing, data engineering, analytics, architecture, data management, or governance, including ownership of production data platforms.
5+ years of experience leading complex data or technology delivery, including roadmap, backlog, financial, vendor, risk, and stakeholder management.
3+ years of people-leadership experience managing multidisciplinary teams and external delivery partners.
Demonstrated experience designing and operating cloud data warehouse or lakehouse platforms using GCP, Microsoft Azure, or AWS.
Experience with conceptual, logical, physical, dimensional, and semantic modeling; source-to-target mapping; slowly changing dimensions; historization; metadata; lineage; and performance-oriented database design.
Strong knowledge of ETL/ELT engineering, SQL, APIs, files, event/stream integration, workflow orchestration, dependency management, error handling, reconciliation, performance tuning, and production support.
Experience implementing CI/CD and DevSecOps practices for data pipelines and infrastructure, including Git-based version control, automated testing, environment promotion, infrastructure as code, release controls, and rollback.
Experience establishing automated data-quality controls, observability, monitoring, alerting, operational SLAs/SLOs, root-cause analysis, incident/problem management, and post-production control frameworks.
Experience leading end-to-end testing and UAT for integrated data solutions, including test strategy, representative data, traceability, regression, reconciliation, defect management, and business sign-off.
Experience managing technology budgets, cloud costs, forecasts, contracts, vendors, and investment cases; working knowledge of FinOps and cloud capacity/cost optimization.
Experience with Agile delivery methods such as Scrum and Kanban, backlog and roadmap management, and tools such as Jira or Azure DevOps.
Experience with BI and visualization platforms such as Microsoft Power BI, Tableau, or Looker, including semantic models, certified datasets, security, and capacity governance.
Experience managing multiple stakeholders and delivery partners in a collaborative, fast-paced enterprise environment.
Ability to translate business strategy, operational processes, analytical questions, and control requirements into integrated data architecture, prioritized roadmaps, executable backlogs, and measurable delivery plans.
Deep understanding of enterprise data architecture, data warehousing, lakehouse patterns, data modeling, ETL/ELT, orchestration, metadata, lineage, governance, semantic layers, data quality, testing, CI/CD, observability, security, and production operations.
Ability to make architecture and investment trade-offs based on business value, data trust, scalability, performance, resiliency, security, maintainability, delivery speed, operating complexity, and total cost of ownership.
Ability to lead through influence across business units and technical, finance, procurement, BI, data science, and vendor teams.
Ability to establish practical operating mechanisms, standards, controls, decision rights, metrics, review cadences, and accountability.
Strong financial, commercial, and vendor-management acumen, including budgeting, forecasting, capacity planning, contract performance, cloud-cost optimization, and investment justification.
Strong program and project leadership skills, including prioritization, dependency management, resource planning, risk mitigation, executive reporting, conflict resolution, and delivery recovery.
Excellent written, oral, presentation, and facilitation skills for communicating technical architecture, delivery risk, cost, quality, and business implications to executive and technical audiences.
Ability to develop people, set expectations, provide candid feedback, build technical depth, retain institutional knowledge, and foster quality, ownership, and continuous improvement.

Nice To Haves

Direct experience with BigQuery and related GCP data services.
Experience with AI/ML data enablement, MLOps, customer identity, master data management, and real-time data products.

Responsibilities

Lead the Enterprise Data team, including employees, consultants, managed-service partners, and cross-functional contributors.
Own the enterprise data warehouse as a technology product and business capability, with accountability for reliability, delivery performance, stakeholder outcomes, platform health, technical debt, security, cost, and continuous improvement.
Define, maintain, and execute the enterprise data warehouse strategy and multi-year roadmap, including architecture, modernization, cloud migration, data products, semantic-layer development, resiliency, and lifecycle management.
Own and govern the consolidated backlog, including intake, sizing, prioritization, dependencies, release planning, and roadmap communications.
Partner with business leaders, product owners, BI teams, and subject-matter experts to gather requirements and translate them into testable epics, features, stories, acceptance criteria, and data contracts.
Lead source-data discovery, profiling, and analysis, ensuring documentation of source meaning, record behavior, change patterns, ownership, quality, lineage, retention, and fitness for use.
Establish and govern enterprise data architecture across ingestion, lake/lakehouse, warehouse, operational data, master and reference data, semantic, analytics, AI, metadata, security, observability, and consumption layers.
Lead data modeling across conceptual, logical, physical, dimensional, relational, and semantic approaches, ensuring consistent definitions, appropriate grain and history, reusable structures, lineage, auditability, performance, and architecture alignment.
Provide technical leadership for ETL/ELT and data integration design and development, including ingestion, cleansing, transformation, mapping, business rules, reconciliation, metadata, error handling, restartability, performance, and maintainable code.
Own integration job orchestration and dependency design across batch, event-driven, API, streaming, and near-real-time workloads.
Establish software-engineering and DevSecOps standards for data solutions, including version control, peer review, testing, infrastructure as code, CI/CD, release approvals, rollback, and deployment.
Define and enforce end-to-end testing covering unit, component, schema, transformation, integration, regression, performance, security, reconciliation, disaster recovery, and user acceptance.
Coordinate UAT with business owners and BI consumers, including test data, expected results, defect triage, sign-off, release readiness, and downstream reporting validation.
Own post-production data-quality controls, 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; turn recurring incidents and temporary fixes into permanent improvements.
Manage data warehouse financials, including operating and capital plans, forecasts, vendor and license spending, cloud consumption, labor mix, business cases, variance management, and investment optimization.
Drive cloud infrastructure and FinOps optimization, including 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, managing scope, schedule, budget, staffing, dependencies, risks, issues, quality, vendors, reporting, change control, adoption, and benefits realization.
Balance strategic delivery, maintenance, production support, governance, and modernization through capacity planning and resource allocation; identify staffing, partner, skill, and knowledge-retention risks.
Lead enterprise data governance execution, including glossary, ownership and stewardship, critical data elements, metadata, lineage, access, privacy, retention, master/reference data, quality, certification, and controlled change.
Manage BI platform administration and future direction with BI leadership, including semantic-model standards, certified datasets, workspace and capacity governance, self-service, security, lifecycle management, and architecture alignment.
Establish architecture, engineering, quality, and delivery review forums, measurable standards, and quality gates; document and manage exceptions, risks, and technical decisions.
Coach and develop team members, set technical and delivery expectations, build succession and skill-development plans, and promote business-domain knowledge, engineering discipline, documentation, collaboration, and accountability.
Perform other duties as assigned.

Benefits

Competitive annual salary; starting base compensation range of $105,147–$167,018.
Annual bonus eligibility.
Hybrid schedule with 3 days on-site weekly.
Comprehensive health benefits package, including medical, dental, and vision plan options.
Generous accrued paid time off, including 2+ weeks of PTO within the first year.
Paid company holidays, including 8 paid holidays.
401(k) plan with company match up to 7%.
Professional development opportunities and continual learning reimbursement up to $5,250 per year.
Tuition reimbursement.
Paid parental leave up to 2 weeks.
Paid time off to volunteer, including 1 volunteer day per year, and company-sponsored volunteer opportunities and events.
Complimentary AAA Membership.
Health and Wellness Program.
Health Concierge Service.
Life insurance and short-term/long-term disability.
Other benefits are referenced but not specified.