Lead Data Architect

We are seeking a highly experienced Lead Data Architect to provide strategic and technical leadership for enterprise data architecture initiatives. This role will oversee a team of data architects and drive the design, governance, and evolution of enterprise data solutions to align with business goals and modernization strategies. The ideal candidate brings deep expertise in cloud data platforms, data modeling, governance, and large-scale data engineering, along with proven leadership experience managing technical teams., * Lead the design and roadmap of enterprise data architecture, including:

• Data warehouses
• Data marts
• Operational data stores
• Ensure alignment of data models and structures with enterprise standards and modernization goals.
• Oversee logical and physical data modeling across systems and programs.
• Direct and review source-to-target mappings for integration and transformation projects.

Team Leadership and Oversight

• Manage, mentor, and guide a team of Data Architects.
• Provide work direction, coaching, and quality assurance of deliverables.
• Allocate resources and prioritize architectural work across projects.
• Establish and enforce best practices, standards, and consistent methodologies.
• Support professional growth and skill development aligned with enterprise strategy.

Data Standards, Quality, and Governance

• Define and enforce data architecture standards, including:
• Metadata management
• Naming conventions
• Data modeling principles
• Data lineage documentation
• Lead development and validation of data quality rules.
• Ensure complete, end-to-end data lineage and traceability.
• Maintain compliance with enterprise governance frameworks and regulatory requirements.

Technical Strategy and Solution Guidance

• Partner with engineering and analytics teams to design scalable data solutions and pipelines.
• Provide expert guidance on:
• Database performance optimization
• Data loading strategies
• Disaster recovery and resiliency
• Influence technology decisions to support modernization and scalability.
• Evaluate emerging tools, technologies, and architecture patterns., * Work with business leaders, architects, and program teams to align data strategies with organizational goals.
• Participate in project intake, solution design, and architectural reviews.
• Promote a data-driven culture focused on data quality, governance, and innovation.

Documentation and Quality Assurance

• Ensure all architectural artifacts (models, mappings, lineage, governance documents) are:
• Accurate
• Accessible
• Maintained to enterprise standards
• Review and approve deliverables to ensure consistency and quality.

Do you have experience in Technology security practices?, * Minimum 7+ years of experience managing large-scale, complex database systems.

• Minimum 7+ years of experience in ETL/data engineering, including:
• At least 3 years with Azure technologies:
• Azure Data Factory (ADF)
• Azure Databricks
• Azure Synapse Analytics
• Azure Purview
• Proven experience leading and managing data architecture or engineering teams.
• Strong expertise in:
• Data modeling and architecture
• Cloud data ecosystems
• Modern data engineering frameworks
• Advanced proficiency in:
• SQL
• Spark
• Python or Scala
• Experience building and optimizing large-scale ETL pipelines.
• Solid understanding of:
• Data governance frameworks
• Data security and RBAC within Azure
• Strong communication and stakeholder engagement skills.

Preferred Qualifications

• Experience with AWS data platforms, including:
• AWS S3
• Data Sync
• Data warehousing solutions
• Knowledge of compliance standards such as:
• Criminal Justice Information (CJI)
• HIPAA, * Leadership: Inspires teams, drives accountability, and promotes excellence.
• Strategic Thinking: Aligns data architecture with long-term business goals.
• Communication: Effectively communicates with both technical and non-technical audiences.
• Problem Solving: Identifies complex challenges and delivers scalable solutions.
• Collaboration: Builds strong partnerships across business and IT teams.
• Innovation: Continuously improves data architecture using modern technologies and practices.