Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, construct, manage, and sustain dependable data pipelines for both structured and unstructured mission and enterprise data.

• Transform historical and operational data into standardized, traceable formats that are ready for machine learning.

• Create and automate batch and real-time ETL/ELT workflows, data integrations, APIs, and orchestration tasks.

• Design and enhance architectures for relational, non-relational, data lakes, warehouses, and lakehouses.

• Execute data profiling, validation, reconciliation, schema management, metadata handling, lineage tracking, monitoring, and quality control measures.

• Collaborate with data scientists, AI/ML engineers, software developers, analysts, and mission stakeholders on datasets utilized for model training, evaluation, deployment, and ongoing support.

• Offer shared support, synchronization, integration, reusable engineering patterns, and best practices across AI/ML teams and data science initiatives.

• Implement access controls, encryption, logging, auditing, and handling protocols to safeguard sensitive government data.

• Monitor and enhance pipelines, resolve integration issues, deliver rapid-response support, and maintain technical, security, operational, and knowledge-transfer documentation, including instructional videos.

⛳️ Requirements

• Bachelor's degree in computer science, data engineering, software engineering, information systems, mathematics, engineering, or a related technical discipline.

• A minimum of five years of professional experience in designing, developing, deploying, and maintaining data pipelines, data platforms, databases, or enterprise data integrations.

• Proven experience in constructing production ETL/ELT pipelines and automated workflows using contemporary data integration, orchestration, version control, testing, and continuous integration methodologies.

• Advanced expertise in Python and SQL, including data transformation, query optimization, scripting, automation, and integration with application or analytical services.

• In-depth knowledge of data modeling and database architecture across relational, non-relational, object storage, data warehouse, data lake, or lakehouse technologies.

• Experience in implementing data quality, schema management, metadata handling, lineage tracking, observability, reconciliation, and repeatable error-handling processes for complex multi-source datasets.

• Understanding of secure data engineering practices, including identity and access management, encryption, logging, auditing, least privilege, and safeguarding sensitive information.

• Experience in producing technical documentation, architecture diagrams, interface specifications, operational procedures, and knowledge transfer materials.

• Capability to work autonomously while collaborating with data science, AI/ML, software, cybersecurity, governance, and operational teams.

• Active SECRET security clearance.

• Must satisfy eligibility criteria for a U.S. Government security clearance; only U.S. citizens are eligible for a security clearance.

🏝️ Benefits

• Salaried

• Comprehensive Fringe/Full-Time benefits

• Equal employment opportunities

• Application-process accommodations for individuals with disabilities