Data Architect SME - CLEARED

The Squires Group•Vienna, VA

20h•Remote

About The Position

Our client is a rapidly growing federal contractor seeking a Data Architect SME. In this role, you will lead the strategic design and evolution of a decentralized data ecosystem, architecting scalable cloud data solutions, advancing data mesh practices, establishing data governance, and enabling self-service analytics and domain-driven data products. This role is remote, with occasional required travel to the DMV if a non-local candidate, or occasional onsite needs if a DMV local candidate. Active Secret Clearance is required.

Requirements

8+ years of hands-on experience in data architecture, including large-scale data lakes, data warehouses, and data mesh environments.
5+ years of experience with cloud-based data platforms and strong expertise in AWS services for data storage, processing, analytics, and governance.
2+ years of leadership experience managing or mentoring data engineering or architecture teams.
Proven experience working in Agile environments using Scrum, Kanban, Jira, Confluence, and SAFe methodologies.
Deep expertise in data governance, metadata management, data lineage, access controls, privacy requirements, and data cataloging.
Strong understanding of decentralized data architecture and data mesh principles, including domain ownership, data as a product, self-service infrastructure, and federated governance.
Excellent communication and stakeholder management skills, with the ability to translate business objectives into technical architecture and vice versa.
Active Secret Clearance is required.

Nice To Haves

Bachelor’s or master’s degree in Computer Science, Information Systems, Data Engineering, or a related technical field preferred.
Relevant cloud, data architecture, or data management certifications preferred.
Experience with additional cloud platforms such as Azure or Google Cloud preferred.
Familiarity with modern data tools such as dbt, Airflow, and Snowflake preferred.
Knowledge of emerging AI/ML-enabled data architecture trends preferred.

Responsibilities

Lead strategic planning, high-level design, and evaluation of data architecture solutions and emerging technologies.
Design and maintain scalable, cloud-based data infrastructure aligned with decentralized data management and data mesh strategies.
Design and implement ETL/ELT pipelines using AWS data services, including S3, Redshift, Glue, Lake Formation, Lambda, Athena, and EMR.
Collaborate with cross-functional data teams to design, deploy, and evolve domain-specific data products.
Establish and continuously improve data governance practices, including data privacy, access controls, data lineage, metadata management, and data quality.
Maintain and enhance data catalogs and governance tools to improve data integrity, discoverability, trustworthiness, and usability.
Lead the implementation and ongoing support of data mesh architecture, ensuring interoperability and effective data flow across decentralized domains.
Ensure high availability, reliability, performance, and operational excellence across the data architecture.
Drive organizational adoption of data mesh principles through training, mentorship, and change management.
Communicate complex technical concepts to technical and non-technical stakeholders and align architecture initiatives with business objectives.
Serve as a subject matter expert in data architecture, data engineering, cloud data platforms, and business-aligned data strategy.
Provide high-level functional design, integration guidance, technical analysis, and implementation recommendations for complex data challenges.
Participate throughout the solution development lifecycle, including planning, analysis, testing, integration, documentation, and stakeholder presentations.
Apply advanced technical and analytical methods to solve complex data engineering and architecture problems.
Work within Agile environments using Scrum, Kanban, Jira, Confluence, and SAFe methodologies.
Provide team-specific training and mentorship to build organizational data engineering and architecture capabilities.