ETL Data Engineer

Responsibilities

• Developing, maintaining, and executing data extraction pipelines to transport data in and out of multiple environments.
• ETL Development and Data Cleansing: Engineering Python-based ETL pipelines to ingest, clean, and optimize large datasets from various sources, refining data quality and processing efficiency.
• Data Preparation: Applying Python and SQL for data cleaning, integration, and exploratory analysis to uncover valuable insights extracted from large volumes of data.
• Data Visualization: Designing and deploying interactive dashboards and reporting in visualization tools (e.g., Tableau, Power BI).
• Improving application performance by optimizing and executing SQL queries to support data handling.
• Loading data into storage systems like databases or data warehouses.
• Maintaining and documenting ETL workflows and recording data movement/changes.
• Working in an Agile environment to rapidly iterate with our clients.
• Cross-functional collaboration: Partner closely with data scientists, data engineers, and application developers to translate complex business requirements into robust technical implementations.

Requirements

• Active Top Secret/SCI (TS/SCI) clearance with a current Polygraph.
• Bachelor’s degree with 3 years of related experience; OR Master’s degree with 1 year of related experience; OR associate’s degree with 6 years of related experience; OR High School diploma/GED with 9 years of related experience.
• Experience performing extract, transformation, load (ETL) development for data pipelines (specifically cyber data); to include integrating, cleansing, and preparing data from sources for analytics and reporting.
• Proficient in data warehousing, data management, programming (e.g., Python), and ETL tools (e.g., Apache NiFi, Pentaho, Kafka).
• Familiarity with the cyber domain.
• Experience designing and maintaining SQL-based data systems and crafting complex queries.
• Experience designing and deploying interactive dashboards and integrating data systems with visualization and analytics platforms using Tableau and/or Power BI.
• Experience with a cloud environment (e.g., GCP, AWS), including its security containerization technologies (e.g., Docker, Kubernetes).
• Language experience with Python.
• Experience with Git-based workflows and code repository platforms such as GitHub.
• Ability to perform API service development.