Data Engineer

Role overview Build and operate data pipelines for a cloud modernization effort replacing a legacy financial system. The work centers on Python-based ingestion and transformation, AWS data services, and dependable handling of large, complex datasets. You’ll collaborate with engineering and stakeholder teams to turn mission and business requirements into secure, maintainable data solutions.

Responsibilities - Design, build, troubleshoot, and maintain data pipelines across the software development lifecycle. - Develop Python workflows to ingest, transform, validate, and deliver structured and semi-structured data from APIs and files. - Build cloud data solutions using AWS Glue, Lambda, S3, and CloudWatch; improve their scale and performance. - Add automated tests, monitoring, logging, error handling, and data quality checks. - Contribute to decisions about integration, storage, data models, performance, and scalability. - Apply access controls and governance practices, document pipeline behavior, and collaborate through code reviews and Agile delivery.

Requirements - At least two years of relevant data engineering, software development, or data integration experience. - Experience with Python transformations or workflow automation and with ETL/ELT pipelines. - Experience consuming APIs and processing formats such as JSON, X12, flat files, or fixed-width files. - Hands-on familiarity with AWS Glue, Lambda, S3, and CloudWatch Logs. - Understanding of data structures, data modeling, validation, error handling, and performance troubleshooting. - Experience writing automated tests with Pytest or a similar framework. - U.S. citizenship and ability to obtain a U.S. Department of War Secret clearance; ability to obtain AWS Cloud Practitioner (or higher) and CompTIA Security+ (or higher) within 30 days of hire.

Nice to have - A bachelor’s degree in computer science or a related engineering field. - Experience in defense, government, or other regulated environments; familiarity with X12/MILS data. - Exposure to Spark, Kafka, Airflow, Step Functions, Terraform, CloudFormation, CI/CD, or DataOps. - AWS certifications or experience with data architecture, schema design, optimization, lineage, or mentoring.

Benefits and work setup - Remote within the continental United States, aligned mainly to East Coast working hours, with some flexibility; travel may be needed three to four times per year. - Health, dental, and vision coverage; FSA, 401(k) match, life and disability insurance, flexible paid time off, and federal holidays off. - Professional development support, including training, certifications, and conferences.