Enterprise Data Architect

UNAVAILABLE; McLean (VA); On-site; USD 150,000 - 190,000; Full time

Job summary

UNAVAILABLE is seeking an Enterprise Data Architect to lead design, governance, and integration of enterprise data across complex environments in McLean, VA. You will guide modeling, standards, and cross‑functional collaboration with engineering, analytics, and product teams.

You will mentor data architects and engineers, supervise data contracts, and drive modernization using lakehouse, data mesh, and event‑driven approaches. Strong communication with executives is essential.

Qualifications

• Bachelor's or Master’s degree in a related technical field.
• 8+ years in data architecture or enterprise information roles.
• Experience with data modeling for analytics, AI/ML, or domain-driven design.
• Familiarity with lakehouse, data mesh, streaming, and multi-cloud.

Responsibilities

• Lead a team of Data Architects and Data Engineers in modeling data for analytics and enterprise integration.
• Develop canonical data models, semantic layers, and metadata structures.
• Guide adoption of data mesh, lakehouse, and event-driven patterns across platforms.
• Set standards for data contracts, lineage, quality, and governance.
• Collaborate with Data Engineering, MLOps, and AI teams to support scalable pipelines.
• Conduct architecture reviews and align with security and modernization roadmaps.
• Mentor junior staff and influence architectural decisions across programs.
• Define reusable architecture artifacts and support pre-sales with solution designs.

Skills

Data architecture

Team leadership

Data governance

Cloud platforms

Data modeling

Stakeholder communication

ETL/ELT design

Education

Bachelor's or Master's in CS/DI/Data Engineering

Tools

ERWin

dbt

Collibra

Databricks

Kubernetes

Job description

Overview

We are seeking an Enterprise Data Architectto 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.

Responsibilities

• 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!

Qualifications

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

• Bachelor’s orMaster’s degree in Computer Science, Data Engineering, Information Systems, Data Architecture, ora relatedtechnical 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.

• Proficiencywith 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 ofdistributed computing frameworks (Spark, Databricks), relational/NoSQL databases, and cloud‑native storage/compute layers.

• Experience designing data integration approaches such as ETL/ELT pipelines, streaming (Kafka/Kinesis/EventHub), CDC, API integration, and virtualization.

• Knowledge of data governance, metadata management, lineage, data quality, and Zero Trust architecture principles.

• Ability to guide cross‑functional teams,facilitatedesign sessions, and influence architectural decisions across programs.

• Strong communicationskills, capable of translating architectural concepts for technical and non‑technical stakeholders, including executive audiences.

• Mentoring experience anda demonstratedability to guide the growth of junior and mid‑level architects/engineers.

• Preferred certifications:

• CompTIA Network+
• AWS Solutions Architect – Associate or Professional
• Azure Data Engineer or Solutions Architect certifications
• Google Professional Data Engineer
• Databricks Data Engineer Professional
• TOGAF, DAMA CDMP, or enterprise architecture certifications