Data Architect SME - CLEARED

Overview

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.

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.

Qualifications

• 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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