Chief Data Engineer

CACI International•Washington, DC

1d•$114,600 - $252,100

About The Position

CACI is seeking an accomplished Chief Data Engineer to support the Department of Homeland Security (DHS) Office of the Inspector General (OIG). This role offers a unique opportunity to lead the technical implementation of an enterprise data platform that centralizes critical investigative, audit, and oversight data to strengthen national security operations. As the Chief Data Engineer, you will architect and lead the development of cloud-based data pipelines that ingest, transform, and integrate data from diverse sources including investigative systems, hotline complaints, DHS component datasets, and external federal data. You will oversee the migration from legacy ETL platforms to modern cloud-native solutions, establish data integration patterns with DHS data fabric and Delta Sharing, and ensure data quality, governance, and security across all pipelines. Leading a team of data engineers, you will coordinate data onboarding priorities, provide technical leadership for complex analytical needs, and enable AI and advanced analytics through authoritative, governed datasets. Working within secure Azure Government environments, you will build the data foundation for a transformational program of national importance. Join us to make a meaningful impact by engineering the data infrastructure that powers next-generation federal oversight capabilities.

Requirements

Bachelor's degree + 15 years of experience in data engineering, data architecture, software engineering, or related field; equivalencies considered (Master's + 12 years; 21 years with no degree; AA + 17 years)
Proven leadership experience architecting and delivering enterprise-scale data integration and ETL/ELT solutions with demonstrated ability to lead data engineering teams
Deep expertise in cloud data engineering using Azure services (Azure Data Factory, Azure Databricks, Azure Data Lake, Azure Synapse) or equivalent AWS/GCP platforms
Extensive hands-on experience with data pipeline development using Python, SQL, PySpark, and modern data integration frameworks with understanding of lakehouse architectures and Delta Lake
Strong background in data architecture, data modeling, data quality, performance optimization, and operationalizing production data pipelines at scale

Nice To Haves

Experience with Informatica PowerCenter, Informatica Data Quality, or other legacy ETL platforms and successful migration to cloud-native solutions
Hands-on experience with DHS data fabric, Delta Sharing, or federal data-sharing mechanisms in secure government cloud environments (Azure Government, AWS GovCloud)
Background in federal government, law enforcement, investigative, or national security data environments with understanding of sensitive data handling, data governance, and compliance requirements (NIST 800-53, FedRAMP)

Responsibilities

Lead the design, development, testing, and implementation of enterprise data ingestion and transformation pipelines that consolidate investigative records, hotline data, DHS datasets, and federal/commercial data sources into a centralized, governed data platform
Oversee migration from legacy Informatica PowerCenter, Informatica Data Quality, and on-premises Python scripts to modern cloud-based data integration solutions using Azure Data Factory, Databricks, or equivalent technologies
Architect and implement scalable data integration patterns supporting batch processing, incremental updates, streaming ingestion, and metadata-driven pipelines with comprehensive error handling and monitoring
Lead ongoing operation, automation, monitoring, and reporting of production data pipelines, including performance optimization, failure remediation, data quality validation, and SLA compliance
Design and implement integration with DHS data fabric, Delta Sharing, APIs, secure file transfer mechanisms, and data-sharing protocols while preserving DHS OIG independence and preventing unauthorized reciprocal access
Coordinate phased data onboarding approach based on Government priorities, including technical discovery, source system analysis, data profiling, pipeline design, testing, and production deployment
Provide technical leadership for data architecture and cloud analytics engineering, including lakehouse design, data modeling (relational, graph, geospatial), and optimization for analytical and AI workloads
Lead and coordinate data engineering resources, including surge support for complex analytical needs, forensic data reconstruction, and specialized technical problem sets
Develop and maintain comprehensive technical documentation including data lineage, pipeline architecture, integration specifications, operational runbooks, and data engineering best practices
Collaborate with Government stakeholders, platform architects, AI engineers, and governance specialists to ensure data pipelines support mission analytics, comply with data governance policies, and enable AI model consumption of authoritative datasets