Data Engineer (DEA)

hatch I.T. is partnering with Expression to find a Data Engineer. See details below: About The Role: Expression is seeking a Data Engineer to support the Drug Enforcement Administration (DEA) Investigative Case and Data Ecosystem (ICDE) modernization effort. This program is focused on modernizing DEA's case management capabilities and creating a centralized, secure, scalable ecosystem supporting law enforcement, investigative, forensic, and intelligence missions. The Data Engineer will design, develop, and maintain scalable data pipelines supporting the ingestion, transformation, migration, validation, and integration of structured and unstructured data. This position will contribute to the modernization and migration of DEA legacy data while helping ensure data is accurate, consistent, secure, and prepared to support analytics and emerging AI/ML capabilities. Location and Clearance: Clearance: Top Secret (SCI) required. Location: Arlington, VA. The program is primarily onsite at DEA Headquarters. About the Company: Founded in 1997 and headquartered in Washington DC, Expression provides data fusion, data analytics, software engineering, information technology, and electromagnetic spectrum management solutions to the U.S. Department of Defense, Department of State, and national security community. Expression’s “Perpetual Innovation” culture focuses on creating immediate and sustainable value for their clients via agile delivery of tailored solutions built through constant engagement with their clients. Expression was ranked #1 on the Washington Technology 2018's Fast 50 list of fastest growing small business Government contractors and a Top 20 Big Data Solutions Provider by CIO Review.

Design, develop, and maintain scalable ETL pipelines for ingesting, transforming, and loading structured and unstructured datasets. Support large-scale migration of legacy data into the modernized DEA investigative and case management ecosystem. Analyze complex data structures and source-to-target mappings to identify opportunities for workflow optimization and automation. Implement data cleaning, standardization, validation, classification, and transformation processes to improve data quality and consistency. Monitor and ensure data accuracy, completeness, consistency, and integrity across systems and platforms. Implement data migration strategies supporting application modernization and transitions across platforms and cloud environments. Develop and execute data validation processes and checkpoints throughout data migration activities. Collaborate with analysts, data scientists, developers, and business partners to translate requirements into effective data engineering solutions. Support data interoperability and exchange across integrated systems. Monitor pipeline performance, troubleshoot operational issues, and improve reliability, scalability, and efficiency. Support data preparation and tagging activities needed for analytics and AI/ML use cases. Participate in Agile development activities, including sprint planning, stand-ups, reviews, and retrospectives. Document data flows, source-to-target mappings, transformation logic, validation processes, and operational procedures.

Bachelor's degree on STEM fields and 2+ years of professional experience. Hands-on experience with data analysis, ETL development, and data migration. Proficiency in SQL, including complex queries, data transformations, and performance tuning. Familiarity with Python for data manipulation, scripting, and workflow automation. Experience with ETL frameworks or orchestration tools such as Apache Airflow, Talend, dbt, or similar technologies. Understanding of data warehousing principles, including dimensional modeling and staging architectures. Exposure to cloud-based data platforms such as AWS Redshift, Google BigQuery, Azure SQL, or similar environments. Ability to perform data profiling, validation, troubleshooting, and root-cause analysis. Ability to clearly document technical processes, data mappings, and transformation logic. Ability to collaborate effectively with engineers, analysts, developers, and business stakeholders.

Experience with AWS, Azure, or Google Cloud Platform. Knowledge of big-data technologies such as Hadoop, Spark, or other distributed-processing frameworks. Experience with data visualization tools such as Power BI, Tableau, or Looker. Familiarity with Git or similar version-control systems. Experience designing automated data workflows or integrating workflow-orchestration tools. Experience supporting large-scale data migration or application-modernization initiatives. Experience working in Agile development environments. Experience supporting Federal Government programs or systems.

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