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.

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