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Posted: 10/19/2026Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in enterprise data warehousing, data architecture, and cloud data solutions, with a strong focus on data governance, quality assurance, and financial management. Proven ability to lead multidisciplinary teams and manage complex data initiatives while ensuring stakeholder satisfaction and operational excellence.
Highest-signal resume keywords
Enterprise Data WarehousingCloud Data SolutionsData GovernanceETL/ELT EngineeringFinancial Management
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Lead all aspects of the Enterprise Data team 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, including reliability, delivery performance, stakeholder outcomes, platform health, technical debt, security, cost, and continuous improvement
- Define and execute the long-term enterprise data warehouse strategy and multi-year roadmap, including architecture, modernization, cloud migration, data products, semantic layers, resiliency, and lifecycle management
- Own and prioritize the consolidated backlog for strategic initiatives, regulatory and control needs, production defects, maintenance, technical debt, upgrades, and business enhancements
- Translate business and nonfunctional requirements into epics, features, stories, acceptance criteria, and data contracts
- Lead source-data discovery, profiling, analysis, documentation, lineage, retention, and fitness-for-use evaluation
- Establish and govern enterprise data architecture across ingestion, lake/lakehouse, warehouse, operational, master/reference, semantic, analytics, AI, metadata, security, observability, and consumption layers
- Lead conceptual, logical, physical, dimensional, relational, and semantic data modeling
- Provide technical leadership for ETL/ELT and data integration design and development
- Own integration 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, security, release approvals, and rollback
- Define and enforce end-to-end testing strategy and coordinate UAT through business sign-off and release readiness
- Own post-production data quality controls, reconciliation, anomaly detection, issue remediation, certification, and control evidence
- Create and maintain production monitoring, alerting, observability, runbooks, support procedures, service measures, and operational dashboards
- Own financial management for the data warehouse environment, including budgets, forecasts, vendor and license spend, cloud consumption, and investment optimization
- Drive cloud infrastructure and FinOps optimization across compute, storage, query processing, orchestration, retention, and BI capacity
- Provide accountable project and program delivery for enterprise data initiatives, including scope, schedule, budget, staffing, risks, 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, metadata, lineage, access, privacy, retention, master/reference data, quality, certification, and change management
- Manage BI platform administration and future direction, including semantic models, certified datasets, workspace and capacity governance, self-service enablement, security, and lifecycle management
- Establish architecture, engineering, quality, and delivery review forums with measurable standards and quality gates
- Coach and develop team members, set expectations, build succession and skill-development plans, and promote engineering discipline and accountability
Requirements
What you’ll need- Bachelor's degree in Computer Science, Information Technology, Data Engineering, Information Systems, Business, or a related field required; 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 responsibilities
- 3+ years of people-leadership experience managing multidisciplinary teams including data architects/modelers, data engineers, analysts, QA/test resources, BI professionals, and external delivery partners
- Experience designing and operating cloud data warehouse or lakehouse platforms using Google Cloud Platform, Microsoft Azure, or Amazon Web Services; direct experience with BigQuery and related GCP data services strongly preferred
- 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
- 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
- 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
Benefits
Comp & perks- 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
- Complimentary AAA Membership
- Health & Wellness Program
- Health Concierge Service
- Life Insurance
- Short Term/Long Term Disability
- Medical, Dental, and Vision plan options
- Up to 2 weeks Paid parental leave
- 2+ weeks of PTO within your first year
- Paid company holidays
- Company provided volunteer opportunities + 1 volunteer day per year
- Continual learning reimbursement up to $5,250 per year
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ArchitectureData ModelingSQLCI/CD PracticesAgile Delivery MethodsData Quality ControlsCloud Cost OptimizationData Integration DesignPerformance TuningRoot-Cause Analysis
Soft Skills
LeadershipStakeholder ManagementCommunicationConflict ResolutionTeam Development
Tools & Technologies
Google Cloud PlatformMicrosoft AzureAmazon Web ServicesBigQueryMicrosoft Power BITableauJiraAzure DevOps
Industry Keywords
Data EngineeringBusiness IntelligenceData ManagementData QualityOperational SLAs/SLOs