Lead Data Architect

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Job Title: Lead Data Architect

Location: McLean, Virginia

Work Arrangement: Hybrid

Overview:

We are seeking a technical leader for our data architecture & engineering function — someone who can design, lead, and evolve our enterprise-scale data platform, data pipelines, and data governance practices. The Lead Data Architect will drive strategic data architecture decisions, build robust, scalable data solutions, and collaborate across technical teams and business stakeholders to deliver data-driven capabilities.

Key Responsibilities:

• Lead the design, development, and maintenance of enterprise data architecture: data pipelines (batch & real-time), data warehouses, data lakes, and storage solutions (relational & non-relational) according to business requirements.
• Develop logical and physical data models (conceptual, logical, physical) that represent business processes and data flows; design data storage structures, schema, metadata frameworks, and data dictionaries.
• Define and enforce data governance, data management policies, data quality standards, security, privacy compliance, and metadata management across the organization.
• Lead and manage ETL/ELT processes and data integration/ingestion pipelines, integrating data from multiple sources (databases, APIs, legacy systems), ensuring data consistency, reliability, and performance.
• Optimize data processing workflows and storage solutions for performance, scalability, maintainability, and cost efficiency.
• Collaborate with data engineers, software developers, business stakeholders, analysts, and other teams to align data architecture strategy with business objectives, and support data-driven decision-making.
• Provide technical leadership, mentoring, and architectural guidance to data engineering teams; review and approve design decisions, code / pipeline implementations, and best practices.
• Evaluate and recommend new/ emerging data technologies, tools, and platforms (e.g., cloud data services, data lakes, big data frameworks), and lead migration/refactoring initiatives from legacy data systems if needed.
• Maintain architecture documentation, data flow diagrams, technical specifications, and data strategy roadmaps; participate in architectural governance and review processes.
  
  

Qualifications / Required Skills:

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or related field (or equivalent experience).
• Significant experience (often 8–15 years) in data architecture, data engineering, or similar roles; with several years in leadership/architect capacity.
• Strong expertise in data modeling (conceptual, logical, physical), database systems (relational and/or NoSQL), data warehousing, data lakes, ETL/ELT, data integration, and data storage solutions.
• Experience with cloud data platforms and services (e.g., AWS, Google Cloud Platform, Azure) — especially if data pipelines/platforms are cloud-based.
• Proficiency in programming/scripting languages commonly used in data engineering / ETL (e.g., SQL, Python, Java) depending on the stack.
• Deep understanding of data governance, security, compliance, metadata management, data quality, and best practices for enterprise data management.
• Excellent communication, stakeholder management, and collaboration skills; ability to lead cross-functional teams and influence architectural decisions.
• Strong analytical, strategic thinking, documentation skills, and ability to plan short-term and long-term data strategy and roadmaps.
• Experience with cloud-native data services (e.g., for Google Cloud Platform: Dataflow, BigQuery, Pub/Sub; or for AWS/Azure equivalents) and building event-driven data pipelines.
• Familiarity with data governance frameworks, master-data management (MDM), metadata/catalog tools, data lineage.
• Experience with big data / streaming / real-time data processing, data analytics, and integration with analytics/BI/reporting platforms.