Data Engineering Product Architect

CACI International

5d•$98,500 - $206,800•Remote

About The Position

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.

Requirements

Experience building scalable data-driven services, data ingestion pipelines, and automation workflows, contributing to high‑reliability cloud solutions at an enterprise scale
Experience working on complicated problems and providing solutions that are creative, yet practical and feasible
Strong communication and problem‑solving skills in dynamic, remote environments
Ability to empathetically work with platform customers (software or data engineering teams) to triage and resolve issues, enable self-service, and introduce improvements based on feedback
Ability to collaborate with data scientists, software engineers, platform engineers, cybersecurity, and product stakeholders to support data platform requirements
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related discipline. Experience will be considered in lieu of a degree
Demonstrated experience working with agile project management tools
Must be able to obtain and maintain a NASA Public Trust background investigation

Nice To Haves

Experience supporting the NASA Web Services Operational Environment
Experience working with industry-standard Enterprise Data Platform applications, such as Databricks, Apache Airflow, or similar technologies
Displays tenacity in the face of hard problems and ambiguous requirements
Interest in driving innovation through independent contributions and strategic guidance of a team of software engineers and data scientists.
Experience supporting Federal government project
Ability to design and document technical solutions related to continuous integration and continuous deployment

Responsibilities

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.