Data Engineering Team Lead Job Listing at SAIC in Arlington, VA (Job ID 2613426)

Description

Description

SAIC is seeking qualified applicants to support a cutting-edge data, analytics, and AI platform. Roles include managing customer relationships, service portfolio and catalog management, software engineering & development, data/AI engineering, IT systems operations, and use case intake and analytics for DoW enterprise-scale mission objectives expected in Spring/Summer 2026.   
Positions are contingent pending contract award. 

Job Responsibilities:  

• Design, build, and maintain the core WDP data infrastructure and pipelines using agentic workflows to streamline operations and enhance automation.  

• Ensure the scalability, reliability, and security of the platform to support data ingestion, processing, storage, and transformation for various consumers, including data tooling teams.  

• Develop enterprise data products accessible via a modern data marketplace, implement a medallion architecture for data storage (bronze, silver, gold zones), and establish self-service inbound and outbound data connection methods.  

• Implement data quality monitoring tools, proactive alerting for pipeline issues, and data drift detection mechanisms.  

• Enforce data security policies, optimize infrastructure for performance and scalability, ensure data backup and recovery, and implement robust data governance policies.  

• Document pipelines, models, and governance standards while ensuring compliance with data privacy and security regulations. 

• Design and develop solutions to complex applications problems, system administration issues, or network concerns. Perform systems management and integration functions. 

Qualifications

• Bachelors and nine (9) years or more experience; Masters and seven (7) years or more experience ; PhD or JD and four (4) years or more experience
• Active TS/SCI Clearance Required

Knowledge, Skills, Abilities, and Competencies: 

• Experience developing large-scale data-intensive systems using Big Data technologies such as Hadoop, Databricks, and Splunk.  

• Expert in designing future-state architectures for AI/ML, data analytics, and enterprise data management, as well as migrating systems to cloud platforms like AWS and Azure to improve scalability, cost-efficiency, and regulatory compliance.  

• Proficient in selecting appropriate databases (HDFS, SQL, NoSQL) and optimizing their performance while managing data lakes, metadata, and governance frameworks to enhance organizational decision-making and data quality.  

• Demonstrated expertise in identifying performance bottlenecks, conducting cost-benefit analyses, and delivering solutions to federal and DoD clients, ensuring alignment with cybersecurity and operational requirements.  

• Skilled in leading multi-disciplinary teams, advising CDOs and CIOs, and leveraging technical tools and strategies to drive digital transformation, improving DevSecOps workflows, and achieving agency missions.