Data Engineer 3 - TS clearance required - Wash DC area

Bow Wave LLCArlington, VA
$90,000 - $96,000Onsite

About The Position

We are seeking a Data Engineer with a Bachelor's Degree and a TS clearance to join our team in the Washington D.C. area. This role involves designing, developing, and maintaining scalable ETL pipelines, analyzing complex data structures, and ensuring data accuracy. You will collaborate with various teams to translate requirements into effective data engineering solutions, monitor pipeline performance, and document technical processes.

Requirements

  • Bachelor's Degree
  • TS clearance required
  • 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.

Nice To Haves

  • 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.

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.
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