Clearance Required: Active Secret or above
Responsibilities:
Responsibilities:
- 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.
8+ years designing large-scale data architectures, 5+ years with cloud data platforms, 2+ years leading data engineering teams, experience with data mesh, data governance, ETL on AWS, and Agile practices.
Key Responsibilities
- designing solutions
- implementing pipelines
- leading teams
Skills & Tools
AWS, S3, Redshift, Glue, Lake Formation, Lambda, Jira, Confluence, SAFe, Scrum, Kanban, Data Mesh
Job Details
- Category: Data and Analytics
- Seniority: Senior Level
- Commitment: Full Time
- Workplace: Remote — United States
- Languages: English
About Intellect Solutions
A technology organization building scalable cloud-based data infrastructure and governance to support analytics and domain data products. — Industry: Information Technology