ETL Engineer

Software Engineer Location: Herndon, Virginia Type: Contract Clearance: Active TS/SCI w/ Polygraph needed to apply Company Overview: Cornerstone Defense is the Employer of Choice within the Intelligence, Defense, and Space communities of the U.S. Government. Realizing early on that our most prized assets are our employees, we continually focus our attention on improving the overall work/life experience they have supporting the mission. Our Team is pushed every day to use their industry leading knowledge to provide end-to-end solutions to combat our nation's toughest and most secure problems. If you are looking for a place to not only be professionally challenged, but encouraged and supported by a company that cares, don't look any further than Cornerstone Defense. Currently seeking a detail-oriented and experienced ETL Engineer to join our data engineering team. The ideal candidate will be responsible for designing, building, and maintaining data pipelines and integration processes that enable reliable, timely, and high-quality data delivery across the organization. This role requires strong technical capabilities, a deep understanding of data architecture, and the ability to collaborate effectively with cross-functional stakeholders. The ideal candidate brings deep expertise in Natural Language Processing (NLP), large-scale data processing, and search/discovery systems, with the ability to lead technical teams and translate mission needs into scalable, production-ready capabilities that deliver operational impact. Development will take place in an iterative fashion using Agile development methodology with input from all levels of stakeholders. The candidate must have the ability to communicate with project team members, user community, and leadership to assess changes and demonstrate iterative progress. Key Responsibilities Design, develop, and maintain ETL/ELT pipelines that support data warehouse, analytics, and application needs. Must be experienced with large data sets [hundreds of thousands of records, GB and TB size data sets] Extract, transform, and load data from various sources into centralized storage solutions. Design and enhance search and discovery platforms across large volumes of structured and unstructured data Perform data ingestion, ETL, and integration across enterprise and multi-source environments Optimize ETL workflows for performance, scalability, and reliability. Conduct data validation, profiling, and quality checks to ensure accuracy and completeness. Troubleshoot and resolve data inconsistencies, pipeline failures, or performance bottlenecks. Build and maintain cloud-native solutions (AWS) aligned to secure and resilient architecture patterns Partner with mission operators, analysts, and senior stakeholders to define requirements and deliver mission-relevant analytics Translate mission needs into technical designs, architectures, and implementation roadmaps, ensuring alignment to operational objectives Deliver clear, compelling visualizations, dashboards, and executive-level briefings that communicate analytic insights and recommendations Provide technical leadership and mentorship, including hands-on development, code review, and team development Own delivery of analytic capabilities from concept through deployment, accreditation, and sustainment Support system accreditation, data governance, and security architecture, ensuring data integrity and compliance within classified environments Mandatory: Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (or equivalent experience). Minimum 6-8 years working in Linux Operating system with updating the system for efficient parallel processing, understanding memory, storage and processing data at scale Minimum 6-8 years in Object Oriented programming. Python is preferred software development language Minimum 6-8 years of demonstrated experience with applications in the Commercial Cloud Services (C2S) environment or an Amazon Web Services cloud environment. Willing to consider substituting C2S if candidate has a minimum 4-6 years of cloud computing technology to include Azure, Oracle, Google, etc. Minimum 4-6 years of demonstrated (Extract, Transform, Load – ETL) with large structured and unstructured raw data sets. Strong experience with ETL tools such as Informatica, Talend, SSIS, AWS Glue, or Azure Data Factory. Proficiency in SQL, including complex queries and query optimization. 6-8 Years of experience with AWS platform including understanding EC2, RCS instance types Strong understanding of data warehousing concepts, data modeling, and schema design. Hands-on experience with scripting languages such as Python, Bash, or PowerShell. Familiarity with relational and NoSQL databases. Experience using version control systems such as Git. Optional: Experience working with big data technologies (e.g., Spark, Hadoop, Databricks). Experience with transformer-based models (e.g., BERT) and modern NLP architectures Background in document exploitation, e-discovery, or large-scale search platforms Experience with multi-modal analytics (OCR, image recognition, text + image fusion) Familiarity with search technologies (Solr, Elasticsearch, Lucene) Experience with containerization and DevSecOps pipelines (Docker, CI/CD) Cloudera or similar big data certifications Experience developing risk scoring, anomaly detection, or predictive analytic models