Chief Data Engineer

CACI International Inc

. Lead the design, development, testing, and implementation of enterprise data ingestion and transformation pipelines .

Posted 9/23/2026full-timeWashington • Washington • United StatesLead💰 $114,600 - $252,100 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in architecting and delivering enterprise-scale data integration solutions, with a strong focus on cloud data engineering and data governance. Proven ability to lead data engineering teams and manage complex data pipelines while ensuring compliance with federal standards.

Highest-signal resume keywords

Cloud Data EngineeringData Integration SolutionsPython ProgrammingData ArchitectureLeadership Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IngestionETL/ELT SolutionsSQLPySparkData ModelingPerformance OptimizationData Quality ValidationData GovernanceDelta LakeMetadata-Driven Pipelines

Soft Skills

CollaborationTechnical LeadershipCommunication

Tools & Technologies

Azure Data FactoryAzure DatabricksAzure Data LakeAzure SynapseInformatica PowerCenterInformatica Data QualityDHS Data FabricDelta Sharing

Industry Keywords

Federal Data SharingSensitive Data HandlingNIST 800-53FedRAMPNational Security Data

Tech Stack

Tools & technologies

AWSAzureCloudETLGoogle Cloud PlatformInformaticaPySparkPythonSQL

About the role

Key responsibilities & impact

Lead the design, development, testing, and implementation of enterprise data ingestion and transformation pipelines
Consolidate investigative records, hotline data, DHS datasets, and federal/commercial data sources into a centralized, governed data platform
Oversee migration from legacy Informatica platforms and on-premises Python scripts to modern cloud-based data integration solutions
Architect scalable batch, incremental, streaming, and metadata-driven data integration pipelines
Lead operation, automation, monitoring, reporting, performance optimization, failure remediation, data quality validation, and SLA compliance for production pipelines
Design and implement integrations with DHS data fabric, Delta Sharing, APIs, secure file transfer mechanisms, and data-sharing protocols
Coordinate phased data onboarding, 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 and relational, graph, and geospatial data modeling
Lead and coordinate data engineering resources, including surge support for complex analytical needs and forensic data reconstruction
Develop and maintain technical documentation, data lineage, pipeline architecture, integration specifications, operational runbooks, and best practices
Collaborate with Government stakeholders, platform architects, AI engineers, and governance specialists to support mission analytics, data governance, and AI model consumption

Requirements

What you’ll need

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
Demonstrated ability to lead data engineering teams
Deep expertise in cloud data engineering using Azure Data Factory, Azure Databricks, Azure Data Lake, Azure Synapse, or equivalent AWS/GCP platforms
Extensive hands-on experience with Python, SQL, PySpark, and modern data integration frameworks
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
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
Background in federal government, law enforcement, investigative, or national security data environments
Understanding of sensitive data handling, data governance, and compliance requirements (NIST 800-53, FedRAMP)

Benefits

Comp & perks

Flexible time off benefit
Robust learning resources
Healthcare benefits
Wellness benefits
Financial benefits
Retirement benefits
Family support benefits
Continuing education benefits
Time off benefits
Competitive compensation
Learning and development opportunities