Chief Data Engineer

Accountabilities:: Lead the design, development, testing, and implementation of enterprise data ingestion and transformation pipelines that consolidate investigative records, hotline data, government datasets, and federal or commercial sources. Oversee migration from legacy Informatica PowerCenter, Informatica Data Quality, and on-premises Python solutions to modern cloud-based technologies such as Azure Data Factory and Databricks. Architect scalable data integration patterns supporting batch processing, incremental updates, streaming ingestion, metadata-driven pipelines, error handling, and monitoring. Lead production operations, automation, monitoring, reporting, performance optimization, failure remediation, data quality validation, and SLA compliance for data pipelines. Design integrations with data fabrics, Delta Sharing, APIs, secure file transfer mechanisms, and other data-sharing protocols while maintaining appropriate access boundaries and security. Coordinate phased data onboarding, including technical discovery, source-system analysis, data profiling, pipeline design, testing, and production deployment. Provide technical leadership for cloud analytics engineering, lakehouse architecture, and relational, graph, and geospatial data modeling. Optimize data platforms and pipelines for analytical and AI workloads, ensuring authoritative datasets are available for advanced analytics and model consumption. Lead and coordinate data engineering resources, including specialized support for complex analytical requirements, forensic data reconstruction, and challenging technical problems. Develop and maintain technical documentation covering data lineage, pipeline architecture, integration specifications, operational runbooks, and engineering best practices. Collaborate with government stakeholders, platform architects, AI engineers, and governance specialists to align data engineering with mission requirements, governance policies, and security standards. Requirements Bachelor’s degree with 15+ years of experience in data engineering, data architecture, software engineering, or a related field; equivalent combinations include a Master’s degree with 12+ years, 21 years without a degree, or an associate degree with 17+ years. Proven leadership experience architecting and delivering enterprise-scale data integration and ETL/ELT solutions, including experience leading data engineering teams. Deep expertise in cloud data engineering using Azure services such as Azure Data Factory, Azure Databricks, Azure Data Lake, and Azure Synapse, or equivalent AWS/GCP technologies. Strong hands-on experience developing data pipelines with Python, SQL, PySpark, and modern data integration frameworks. Strong understanding of lakehouse architectures and Delta Lake. Extensive experience with data architecture, data modeling, data quality, performance optimization, and production data pipelines operating at scale. Experience with legacy ETL platforms such as Informatica PowerCenter or Informatica Data Quality, including successful modernization or migration to cloud-native solutions, is preferred. Experience with government data fabrics, Delta Sharing, or federal data-sharing mechanisms in secure cloud environments such as Azure Government or AWS GovCloud is preferred. Background in federal government, law enforcement, investigative, or national security data environments is an advantage. Understanding of sensitive data handling, data governance, and compliance frameworks such as NIST 800-53 and FedRAMP is preferred. Strong technical leadership, communication, collaboration, problem-solving, and documentation skills. Benefits Proposed salary range of $114,600–$252,100, with final compensation influenced by geographic location, contract requirements, experience, skills, education, and certifications. Full-time, regular employment. Hybrid work opportunity in Washington, DC, with remote work available from any U.S. state according to the source listing. Comprehensive healthcare benefits. Wellness programs and support. Financial and retirement benefits. Family support benefits. Flexible time-off options. Continuing education and learning and development opportunities. Opportunity to lead enterprise-scale cloud data engineering and modernization initiatives. Exposure to Azure Government, lakehouse architectures, AI-enabled analytics, data governance, and secure federal data environments. Leadership responsibility across complex data engineering resources and mission-critical technical initiatives. Opportunity to contribute to federal investigative, audit, oversight, and national security data capabilities.