Data Engineer 3 - TS clearance required - Wash DC area with Security Clearance

Education Requirement: Bachelor's Degree Key Responsibilities

• 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.

Required Skills & Experience

• 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.

• 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