ETL Engineer

Title: Software Engineer Location: Herndon, Virginia Clearance: Active TS/SCI with Polygraph required to apply Key Responsibilities Design, develop, and maintain ETL/ELT pipelines that support data warehouse, analytics, and application needs. 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 Qualifications 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 experience optimizing parallel processing, memory, storage, and processing data at scale. Minimum 6‑8 years in Object‑Oriented programming, with Python preferred. Minimum 6‑8 years of demonstrated experience with applications in the Commercial Cloud Services (C2S) environment or Amazon Web Services (AWS). Will consider substitutes with a minimum 4‑6 years experience in Azure, Oracle, Google, etc. Minimum 4‑6 years of demonstrated (Extract, Transform, Load - ETL) experience 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 Skills Experience working with big data technologies (Spark, Hadoop, Databricks). Experience with transformer‑based models (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. #J-18808-Ljbffr