Data Engineering Product Architect
Job Title: Data Engineering Product ArchitectJob Category: EngineeringTime Type: Full timeMinimum Clearance Required to Start: Public TrustEmployee Type: RegularPercentage of Travel Required: Up to 10%Type of Travel: Continental US* * *
The Opportunity:
The Opportunity: CACI’s growing Agile Digital Solutions Operating Group is searching for a Data Engineering Product Architect supporting the modernization and transformation of a large portfolio of enterprise business solutions used by the National Aeronautics and Space Administration (NASA). The candidate will be part of a team where complex problem solving, and communication skills are critical to success.
Responsibilities:
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Lead the design, build, optimization, and maintenance of scalable ETL pipelines
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Guide the development of normalization and transformation frameworks to standardize disparate datasets for analytics, cybersecurity, and mission operations.
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Champion the development of high‑quality, modern, and fully reproducible code using established software engineering practices — including version control, modular design, automated testing, documentation, and CI/CD—to ensure reliability, reusability, and maintainability across data pipelines and Databricks workflows.
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Mentor and coach team on software engineering design principles to help improve code quality and design by team members over time
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Develop solutions within a secure cloud-based architecture leveraging Databricks Lakehouse features (Unity Catalog, Delta Lake, Auto Loader, cluster configuration).
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Manage environment setup, version control, deployment, and CI/CD processes for data pipelines and Databricks apps.
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Develop and maintain integrations between Databricks and enterprise systems through APIs, S3 ingestion endpoints and database connectors.
Collaborate with cross-functional engineering, cybersecurity, and product teams to design and implement features that improve data ingestion, metadata management, automation workflows, and platform usability
-
Document technical requirements, user stories, and workflow specifications for data integrations and interface development.
-
Help scrum master and teammates estimate, sequence, and prioritize work to ensure efficient delivery of prioritized development capabilities
Qualifications:
Required:
-
Lead the design, build, optimization, and maintenance of scalable ETL pipelines
-
Guide the development of normalization and transformation frameworks to standardize disparate datasets for analytics, cybersecurity, and mission operations.
-
Champion the development of high‑quality, modern, and fully reproducible code using established software engineering practices — including version control, modular design, automated testing, documentation, and CI/CD—to ensure reliability, reusability, and maintainability across data pipelines and Databricks workflows.
-
Mentor and coach team on software engineering design principles to help improve code quality and design by team members over time
-
Develop solutions within a secure cloud-based architecture leveraging Databricks Lakehouse features (Unity Catalog, Delta Lake, Auto Loader, cluster configuration).
-
Manage environment setup, version control, deployment, and CI/CD processes for data pipelines and Databricks apps.
-
Develop and maintain integrations between Databricks and enterprise systems through APIs, S3 ingestion endpoints and database connectors.
-
Collaborate with cross‑functional engineering, cybersecurity, and product teams to design and implement features that improve data ingestion, metadata management, automation workflows, and platform usability
-
Document technical requirements, user stories, and workflow specifications for data integrations and interface development.
-
Help scrum master and teammates estimate, sequence, and prioritize work to ensure efficient delivery of prioritized development capabilities.
Qualifications:
Required