Data Engineer 3 - TS clearance required - Wash DC area

*Design, develop, and maintain scalable ETL pipelines for ingesting, transforming, and loading structured and unstructured datasets. *Analyze complex data structures and source-to-target mappings to identify opportunities for workflow optimization and automation. *Monitor and ensure data accuracy, consistency, and integrity across systems and platforms. *Implement data migration strategies to support application modernization and transitions across platforms or cloud environments. *Collaborate with analysts, data scientists, developers, and business partners to translate requirements into effective data engineering solutions. *Monitor pipeline performance, troubleshoot operational issues, and enhance reliability, scalability, and efficiency. *Document data flows, transformation logic, and operational procedures for maintainability and knowledge sharing.

*2+ Years Professional Experience *Hands-on experience with data analysis, ETL development, and data migration. *Proficiency in SQL, including writing complex queries, 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. *Understanding of data warehousing principles including dimensional modeling and staging architecture. *Exposure to cloud-based data platforms such as AWS Redshift, Google BigQuery, Azure SQL, or similar environments. Preferred Qualifications *Experience with cloud ecosystems such as AWS, Azure, or Google Cloud Platform. *Knowledge of big data technologies (Hadoop, Spark, or distributed processing frameworks). *Exposure to data visualization tools (Power BI, Tableau, Looker) and version control systems (e.g., Git). *Experience designing automated data workflows or integrating workflow orchestration tools. Core Skills & Competencies *ETL pipeline development & optimization *SQL & Python for data processing *Data modeling and profiling *Understanding of data warehousing concepts *Cross-functional collaboration *Problem-solving & root cause analysis *Ability to document technical processes clearly *Continuous improvement mindset