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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** 540 - **Location:** United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Agile Methodology, Airflow, Amazon Web Services, Amazon S3, Automation of Tests, Big Data, Command-Line Interface, Code Review, CompTIA Security+, Data Architecture, Data Validation, Information Engineering, Data Governance, Data Integration, Data Integrity, Extract Transform Load (ETL), Data Transformation, Data Security, Data Structures, Data Systems, Software Debugging, DevOps, Distributed Computing Environment, Document-Oriented Databases, JSON, Python (Programming Language), Meta-Data Management, Performance Tuning, Cloud Services, DataOps, Simple Data Format, Software Engineering, Data Logging, Data Processing, Apache Spark, Database Performance, AWS Lambda, Indexer, Gitlab, Cloudformation, SC Clearance, Pytest, Semi-structured Data, Infrastructure Automation Frameworks, Information Technology, Data Lineage, Atlassian Tools, AWS Glue, Data Analytics, Apache Kafka, Functional Programming, Cloudwatch, Terraform, Software Version Control, Data Pipelines - **Published:** October 15, 2026 - **Apply:** https://job-boards.greenhouse.io/540/jobs/8033199003 ## About the Role Citizenship & Clearance Requirement: per client requirements, must be a U.S. Citizen with the ability to obtain a DoW Secret clearance Education Requirement: Bachelor's Degree in Computer Science or related engineering field (preferred) 540 Internal Thrive Level: Data Engineer II or III, * 2+ years of related experience in data engineering, software development, data integration, or a closely related field * Experience developing Python-based data transformations, scripts, or workflow automation * Hands-on experience building, maintaining, or troubleshooting data pipelines and ETL/ELT processes * Experience consuming data from APIs and working with file formats such as X12, JSON, flat files, or fixed-width files * Experience working with AWS cloud services, particularly AWS Glue, AWS Lambda, Amazon S3, and CloudWatch Logs * Familiarity with working with large datasets, including identifying and troubleshooting data processing or performance issues * Understanding of data structures, data modeling concepts, and common approaches to organizing and transforming data * Experience writing and maintaining automated tests using Pytest or similar testing frameworks * Familiarity with data validation, error handling, logging, and debugging practices * Understanding of data security, access controls, and data quality principles * Experience using GitLab for version control and collaborative development * Comfortable working through the terminal or command-line interface * Experience using Jira and Confluence in an Agile development environment * Ability to interpret ambiguous requirements, file specifications, and JSON structures to develop functional data solutions * Strong problem-solving skills and ability to collaborate effectively with technical and non-technical stakeholders * Must currently possess or have the ability to obtain an AWS Cloud Practitioner certification (or higher) within 30 days of hire * Must currently possess or have the ability to obtain a CompTIA Security+ certification (or higher) within 30 days of hire NICE TO HAVE * Experience working with DoW systems, data, or other regulated environments * Familiarity with X12/MILS processing * Experience with Apache Spark, Kafka, or other distributed data processing frameworks * Knowledge of data orchestration tools such as Apache Airflow or AWS Step Functions * Exposure to Infrastructure-as-Code tools, including Terraform or CloudFormation * Understanding of DevOps and DataOps practices, including CI/CD pipelines * AWS certifications such as Solutions Architect, Data Analytics, or similar * Experience developing reusable pipeline components or improving established engineering patterns * Experience contributing to data architecture decisions, schema design, or pipeline performance optimization * Familiarity with database performance optimization, indexing, or partitioning strategies * Experience with data lineage, metadata management, or data cataloging tools * Experience providing technical guidance, mentoring teammates, or contributing to engineering best practices * Familiarity with AI-assisted development tools for coding, testing, documentation, or workflow automation ## Description In this role, you'll design, build, and maintain scalable data pipelines and cloud-native data solutions, with a focus on data reliability, security, governance, and performance. You'll work with large, complex datasets, contribute to technical design decisions, and collaborate across engineering teams to transform business and mission requirements into working software., * Design, build, maintain, and troubleshoot reliable data pipelines throughout the software development lifecycle, supporting the modernization of legacy U.S. Army financial systems and migration to AWS cloud environments * Develop Python-based workflows to ingest, transform, validate, and deliver structured and semi-structured data * Build and support cloud-native data solutions using AWS services such as Glue, Lambda, S3, and CloudWatch * Integrate data from multiple systems and sources, including APIs and various file formats, while supporting data accuracy, consistency, and reliability * Work with large datasets, identify performance bottlenecks, and help improve pipeline efficiency and scalability * Participate in technical design discussions and contribute to decisions around data integration, storage, performance, and scalability * Implement automated testing, logging, monitoring, and error handling to support data quality and reliable system performance * Write clean, reusable, and maintainable code while following established software engineering and DataOps practices * Collaborate with engineers, architects, and stakeholders to translate business and technical requirements into working software * Support secure data management practices, including access controls, data governance, and compliance with DoW requirements * Participate in code reviews and Agile development activities, sharing ideas and contributing to engineering improvements * Document data transformations, pipeline processes, and technical decisions to support maintainability and downstream users * Identify opportunities to improve existing workflows, reduce manual processes, and strengthen the reliability of the Army's data ecosystem