Enterprise Data Lead

REV LLC•Seattle, WA

1d•$95 - $110•Hybrid

About The Position

REV is seeking an experienced Enterprise Data Lead to provide program-level leadership over data strategy, architecture, standards, quality, governance, and cross-platform data decisions for a large-scale modernization initiative. The Enterprise Data Lead will ensure data architecture and data-related decisions remain aligned with business objectives, modernization goals, enterprise standards, security requirements, and long-term sustainability.

Requirements

Bachelor's degree is required.
Bachelor's degree must include at least 12 semester hours or 18 quarter hours of computer science coursework.
Candidate must be able to provide documentation verifying the degree and specific computer science coursework completed if requested.
7+ years of professional IT experience involving IT analysis, data analysis, system design, data management, system maintenance, or enterprise data environments.
5+ years of hands-on data leadership involving enterprise data architecture, strategy, governance, migration, or data management.
Strong experience with enterprise data architecture and data management.
Experience with enterprise data models, data flows, governance, metadata, and lineage.
Experience with data integration, data quality, migration, and conversion patterns.
Experience with MDM, survivorship rules, harmonization, and authoritative sources of truth.
Strong experience with SQL, NoSQL, and cloud data technologies.
Experience with APIs, ETL/ELT, messaging, event-driven pipelines, and service-oriented architectures.
Hands-on experience with Azure, AWS, and/or GCP.
Experience with cloud data storage, processing, serverless functions, and data security controls.
Familiarity with Docker and Kubernetes.
Experience with Java, C#, Python, NodeJS, and/or comparable technologies.
Strong understanding of Zero Trust, encryption, authentication, authorization, privacy, and data security.
Deep understanding of the data lifecycle.
Strong strategic thinking, analytical ability, and executive communication skills.
Must be comfortable working as an individual 1099 Independent Contractor.
Must be willing and able to work onsite in Washington State as required.
Must be able to complete required background screening, security training, confidentiality requirements, and system-access requirements.

Nice To Haves

Large-scale enterprise modernization.
Enterprise-wide data strategy.
Cloud migration.
Enterprise data governance.
MDM implementations.
Public-sector or regulated environments.
Mainframe or legacy system modernization.
Enterprise metadata and data quality programs.
Complex multi-vendor technology environments.

Responsibilities

Maintain enterprise data architecture, standards, patterns, and reference models.
Lead enterprise data design reviews.
Establish data architectural principles and standards.
Provide strategic direction across data domains, platforms, integrations, analytics, and operational systems.
Ensure security, privacy, compliance, and risk principles are embedded into data designs.
Guide data architecture, modeling, canonical data models, and cross-platform data flows.
Evaluate modern data technologies, platforms, tooling, and architectural patterns.
Identify data gaps, redundancies, risks, technical debt, and modernization opportunities.
Drive alignment among vendors, technical teams, business stakeholders, and enterprise leadership.
Support strategic data planning and long-term data model evolution.
Establish and maintain data lifecycle-management strategies.
Oversee data architecture documentation, lineage diagrams, data dictionaries, mapping artifacts, and reference models.
Ensure vendor-produced data documentation meets enterprise standards.
Support data governance, data quality, MDM, migration, integration, and analytics initiatives.
Participate in Agile ceremonies, sprint reviews, architecture reviews, and design discussions.
Support RAID management and data-related risk mitigation.
Provide executive-level technical guidance and recommendations.
Mentor and guide data architects, engineers, analysts, and technical teams.