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Data Architect/Program Lead

Intellect Solutions

Remote, USA

Full-time

Senior · 8+ years experience

Remote

Discovered 6 days ago

AWSS3RedshiftGlueLake FormationLambda

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Participates in planning, definition, and high-level design of data solutions, exploring alternatives and evaluating new technologies.
Develops and maintains scalable cloud-based data infrastructure, ensuring alignment with the organization's decentralized data management strategy.
Designs and implements ETL pipelines using AWS services (e.g., S3, Redshift, Glue, Lake Formation, Lambda) to support data domain requirements and self-service analytics. Procurement Sensitive- See FAR 2.101 and 3.104 21
Collaborates with data domain teams to design and deploy domain-specific data products, adhering to organizational standards for schema design, data transformations, and storage solutions.
Establishes and enforces data governance practices, including compliance with data privacy, access controls, and lineage requirements, across the organization’s data assets.
Maintains a comprehensive data catalog and governance tools, automating workflows to uphold data integrity and ensure discoverability across all domains.
Leads the implementation and ongoing support of data mesh architecture, ensuring seamless integration and data flow across multiple domains.
Ensures the availability and reliability of the organization’s Data Mesh software, managing operations and maintenance of the framework.
Provides guidance and leadership on the cultural adoption of data mesh principles, including organizational training initiatives for data stewards and users.
Communicates effectively with stakeholders to align technical data architecture with business goals, ensuring long-term support for analytics, insights, and innovation.
Experience working in an Agile organization using Scrum, Kanban, Jira, Confluence, and SAFe.
Provide team specific training as needed.
Experience in Data Architecture: Minimum of eight (8) years of experience designing and implementing data architectures, including large-scale data environments such as data lakes, data warehouses, and data mesh frameworks.
Experience with Cloud Platforms: Minimum of five (5) years of experience working with cloud-based data platforms (e.g., AWS, Azure, Google Cloud), particularly for data storage, processing, and analytics.
Leadership and Team Management: Demonstrated two (2) years of experience leading and mentoring data engineering teams, fostering collaboration, and ensuring successful project execution.
Education: A bachelor’s or master’s degree in computer science, Information Systems, Data Engineering, or a related technical field, preferred.