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Lead Data Architect

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Remote, Hybrid

Lead Data Architect

The Amatriot Group

Lead Data Architect

Skills

Google Cloud PlatformData EngineeringAWS LambdaAmazon RedshiftData AnalysisAWSJiraConfluenceGoogle AnalyticsKanbanComplianceAzure

2 months ago

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Important information


Contract type:

Permanent

Salary:

$150,000 – $170,000 / year

Location:

United States

Work mode:

Remote, Hybrid

Published on:

23 September 2026

What they need


Location: Hybrid, 1 day a week onsite Tysons Corner, VA
Clearance: Active Secret or Above
Job Type: Full-Time
Target Salary Range*:$150,000 - $170,000

  • This represents the potential salary range for this position depending on education level, years of experience and/or certifications in addition to other position specific requirements which may impact salary

Position Overview

The Data Architect supports planning, design, implementation, governance, and sustainment of scalable cloud-based data solutions. This role develops data infrastructure, supports domain-specific data products, implements data mesh architecture, and aligns technical data architecture with business goals to support analytics, insights, and innovation.

Key Responsibilities

Data Architecture and Solution Design

  • Participate in planning, definition, and high-level design of data solutions.
  • Explore alternatives and evaluate new technologies.
  • Develop and maintain scalable cloud-based data infrastructure.
  • Ensure data infrastructure aligns with the organization’s decentralized data management strategy.
  • Communicate effectively with stakeholders to align technical data architecture with business goals.

ETL, Cloud Data Platforms, and Data Products

  • Design and implement ETL pipelines using AWS services, including S3, Redshift, Glue, Lake Formation, and Lambda.
  • Support data domain requirements and self-service analytics.
  • Collaborate with data domain teams to design and deploy domain-specific data products.
  • Adhere to organizational standards for schema design, data transformations, and storage solutions.

Data Governance and Catalog Management

  • Establish and enforce data governance practices, including compliance with data privacy, access controls, and lineage requirements.
  • Maintain a comprehensive data catalog and governance tools.
  • Automate workflows to uphold data integrity and ensure discoverability across all domains.

Data Mesh Implementation and Operations

  • Lead the implementation and ongoing support of data mesh architecture.
  • Ensure seamless integration and data flow across multiple domains.
  • Ensure the availability and reliability of the organization’s Data Mesh software.
  • Manage operations and maintenance of the Data Mesh framework.

Agile Collaboration, Training, and Leadership

  • Apply experience working in an Agile organization using Scrum, Kanban, Jira, Confluence, and SAFe.
  • Provide guidance and leadership on the cultural adoption of data mesh principles.
  • Support organizational training initiatives for data stewards and users.
  • Provide team-specific training as needed.

Qualifications

Education

  • Bachelor’s or master’s degree in Computer Science, Information Systems, Data Engineering, or a related technical field preferred.

Experience

  • Minimum 8 years of experience designing and implementing data architectures, including large-scale data environments such as data lakes, data warehouses, and data mesh frameworks. [Required]
  • Minimum 5 years of experience working with cloud-based data platforms, such as AWS, Azure, or Google Cloud, particularly for data storage, processing, and analytics. [Required]
  • 2 years of demonstrated experience leading and mentoring data engineering teams, fostering collaboration, and ensuring successful project execution. [Required]
  • Experience working in an Agile organization using Scrum, Kanban, Jira, Confluence, and SAFe.

Skills

  • Ability to design and maintain scalable cloud-based data infrastructure.
  • Ability to design and implement ETL pipelines using AWS services.
  • Ability to establish and enforce data governance practices.
  • Ability to maintain data catalogs and governance tools.
  • Ability to support data mesh architecture, integration, operations, and maintenance.
  • Ability to communicate effectively with stakeholders.
  • Ability to provide guidance, leadership, and team-specific training.

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