Manager, Enterprise Data

AAA Mid-Atlantic • Cincinnati, OH

1d • $105,147 - $167,018 • 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 business capability. The role is accountable for platform reliability, delivery performance, stakeholder outcomes, technical health, security, costs, and continuous improvement. It leads employees, consultants, managed-service partners, and cross-functional contributors across data analysis, 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, covering architecture, modernization, cloud migration, technical debt, data products, semantic layers, resiliency, and lifecycle management. The role governs the consolidated backlog and delivery approach for strategic initiatives, controls, defects, maintenance, upgrades, and business enhancements, while partnering with business leaders and technical stakeholders to translate needs into testable requirements and data contracts.

The position establishes enterprise data architecture and modeling standards, leads source-data discovery and ETL/ELT and integration engineering, and owns orchestration across batch, event-driven, API, streaming, and near-real-time workloads. It sets engineering, DevSecOps, testing, UAT, data-quality, monitoring, observability, and production-support practices, ensuring traceability, reliable releases, operational controls, and ongoing remediation of issues.

The role also manages data warehouse financials, cloud infrastructure and FinOps optimization, enterprise project and program delivery, resource planning, data governance, and BI platform administration and direction. It establishes review forums and quality gates, manages risks and technical decisions, and coaches team members while developing their skills 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.
• At least 8 years of progressive experience in enterprise data warehousing, data engineering, analytics, architecture, data management, or governance, including ownership of production data platforms.
• At least 5 years of experience leading complex data or technology delivery, including roadmap, backlog, financial, vendor, risk, and stakeholder management.
• At least 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 Google Cloud Platform, Microsoft Azure, or Amazon Web Services.
• 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 principles 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 an integrated data architecture, prioritized roadmap, executable backlog, and measurable delivery plan.
• 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 sound 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, including communication of 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 create a culture of quality, ownership, and continuous improvement.

Nice To Haves

• Direct experience with BigQuery and related Google Cloud Platform 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, stakeholder outcomes, platform health, security, cost, and continuous improvement.
• Define and execute the long-term enterprise data warehouse strategy and multi-year roadmap.
• Own the consolidated backlog, including 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 requirements and translate them into epics, features, stories, acceptance criteria, and data contracts.
• Lead source-data discovery, profiling, and analysis, and ensure documentation of source meaning, behavior, ownership, quality, lineage, retention, and fitness for use.
• Establish and govern enterprise data architecture across ingestion, storage, warehouse, operational, master and reference data, semantic, analytics, AI, metadata, security, observability, and consumption layers.
• Lead conceptual, logical, physical, dimensional, relational, and semantic data modeling, ensuring consistent definitions, appropriate grain and history, reusable structures, lineage, auditability, performance, and standards alignment.
• Provide technical leadership for ETL/ELT and data integration design and development, including ingestion, transformation, reconciliation, metadata capture, error handling, restartability, and performance tuning.
• 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, testing, infrastructure as code, CI/CD, release approvals, rollback, and production deployment.
• Define and enforce end-to-end testing strategy, with traceability from requirements and source-to-target rules through test evidence and release approval.
• Coordinate UAT with business owners and BI consumers, including test data, expected results, defect triage, sign-off, release readiness, and downstream validation.
• Own the post-production data-quality control framework, including controls, reconciliation, anomaly detection, exception workflows, root-cause analysis, remediation, certification, and evidence.
• Create and maintain production monitoring, alerting, observability, runbooks, support procedures, service measures, and operational dashboards.
• Ensure recurring incidents and temporary fixes are converted into backlog items and permanent improvements.
• Own financial management for the data warehouse environment, including budgets, forecasts, vendor and license spend, cloud consumption, labor mix, business cases, 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, quality, vendors, reporting, change control, adoption, and benefits realization.
• Balance strategic delivery, maintenance, production support, governance, and modernization through capacity planning and resource allocation.
• Lead enterprise data governance execution, including glossary, ownership, stewardship, critical data elements, metadata, lineage, access, privacy, retention, master/reference data, quality standards, certification, and change management.
• Manage BI platform administration and future direction in coordination with BI leadership.
• 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 expectations, build succession and skill-development plans, and promote domain knowledge, engineering discipline, documentation, collaboration, and accountability.
• Perform other duties as assigned.

Benefits

• Competitive annual salary; starting base compensation is $105,147–$167,018.
• Annual bonus eligibility.
• Hybrid schedule with 3 days on-site weekly.
• Comprehensive health benefits, including medical, dental, and vision plan options.
• Generous accrued paid time off, including 2+ weeks of PTO within the first year.
• 8 paid holidays and paid company 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 time off to volunteer, company-sponsored volunteer events, and one volunteer day per year.
• Complimentary AAA Membership.
• Health and Wellness Program.
• Health Concierge Service.
• Life Insurance.
• Short-term and long-term disability.
• Up to 2 weeks of paid parental leave.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager