Our client is a rapidly growing federal contractor. They are 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. Per our client contract, Active Secret Clearance is required. 

• 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.

• 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.
• 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.

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