Enterprise Data Architect

We are seeking an Enterprise
Data Architect
to guide the design, development, and governance of enterprise data architectures across complex mission environments. This role combines hands‑on architecturalexpertisewith team leadership, oversight of data modeling and integration patterns, and cross‑functional coordination with engineering, analytics, AI, and product teams. The Data Architecture Team Lead ensures that data is modeled, structured, governed, and integrated in ways that maximize interoperability, usability, and long‑term platform scalability.

• Lead a team of Data Architects and Data Engineers in designing conceptual, logical, and physical data models that support analytics, AI/ML, operational applications, and enterprise integration needs.

• Develop andmaintaincanonical data models, semantic layers, metadata structures, and domain‑oriented schemas aligned with enterprise data strategies.

• Guidethe adoption of modern architectural patterns includinglakehouse, data mesh, data fabric, domain‑driven design, and event‑driven integration.

• Establish standards for data modeling, schema evolution, semantic consistency, and data contract design across teams and systems.

• Partner with Data Engineering,MLOps/LLMOps, and AI Development teams to ensure dataarchitecturessupport scalable pipelines, feature engineering, and high‑performing ML/AI workloads.

• Conduct data architecture reviews, ensuring alignment with enterprise reference architectures, security principles, performance expectations, andmodernizationroadmaps.

• Lead integration strategy across platforms, including API‑driven data access, streaming and event frameworks, CDC pipelines, virtualization layers, and metadata‑driven automation.

• Work with mission stakeholders, product teams, and UX researchers to translate requirements into well‑designed data structures that support workflows and decision‑making.

• Oversee governance‑aligned design practices, including lineage, cataloging, data quality frameworks, tagging strategies, and Zero Trust data‑access patterns.

• Mentor Data Architects and senior Data Engineers, elevating architectural thinking, modeling capabilities, and technical decision‑making across the team.

• Evaluate emerging technologies—metadata platforms, data modeling tools, data virtualization engines, event brokers—and guide strategic adoption.

• Contribute to reusable architectural artifacts including reference models, standards, playbooks, integration patterns, and platform design templates.

• Support pre‑sales and proposal efforts by defining solution architectures, estimating delivery complexity, and articulating modernization strategies.

• You will contribute to the growth of our AI & Data Exploitation Practice!

• Ability to hold a position of public trust or higher clearance as required.

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Data Architecture, ora related technical field.

• 8+ years of experience in data architecture, data engineering, or enterprise information architecture roles.

• Strong experience designing conceptual, logical, and physical data models for analytical, transactional, or domain‑driven applications.

• Proficiency with modern data platforms and architectural patterns includinglakehouse, data warehouse, data mesh, streaming architectures, and multi‑cloud ecosystems (AWS, Azure, GCP).

• Hands‑on experience with modeling and metadata tools (e.g.,ERWin, ER/Studio,dbt, Collibra, Alation, Atlan, or similar).

• Understanding of distributed computing frameworks (Spark, Databricks), relational/No
  
  SQL databases, and cloud‑native storage/compute layers.

• Experience designing data integration approaches such as ETL/ELT pipelines, streaming (Kafka/Kinesis/Event Hub), CDC,…