Build, optimize, and maintain batch and real-time data ingestion pipelines
Lead design and implementation of scalable ETL processes across complex, distributed systems
Develop and manage data lake architecture for structured and unstructured data
Utilize AWS services (EventBridge, S3 Event Notifications) for workflow orchestration and scheduling
Use AWS Glue, Python, and SQL to transform and prepare data for downstream consumption
Ensure data quality, lineage, governance, and compliance across all systems
Work closely with software team and data scientists to support reporting and model development
Mentor junior engineers, providing technical guidance and peer reviews
Document data pipelines, standards, and data product specifications

Must be a U.S. Citizen.
Bachelor’s degree in computer science or related field, with a minimum of three (3) years of relevant work experience.
An active security clearance or the ability to obtain one is required.
Strong proficiency in Python and SQL
Hands-on experience with Pandas, PySpark, and AWS Glue
Deep understanding of ETL frameworks, data lake design, and cloud-based architecture
Familiarity with real-time and batch data processing tools and methodologies
Experience with data governance, security compliance, and maintaining data quality standards.

Mid Data Engineer

Key skills