{"id":3489694,"url":"https://alion.io/job/inflow-federal-data-engineer","title":"Data Engineer","company":{"id":678779,"name":"INflow Federal","domain":"inflowfed.com","url":"https://alion.io/company/inflowfed","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"C","score":60,"open_postings":21,"ghost_share":0.667,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":53,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":70000,"max":90000,"currency":"USD","period":"year","gross":null,"usd_annual":90000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache NiFi","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"CI/CD","optional":false},{"name":"DynamoDB","optional":false},{"name":"ETL/ELT","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Talend","optional":false}],"status":"live","first_seen_at":"2026-05-12T12:34:04Z","employer_posted_date":"2026-05-12","last_verified_at":"2026-10-31T00:55:36Z","board_verified":true,"closed_at":null,"days_open":171,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":171},"description":"INflow Federal is seeking a Data Engineer to design, develop, and maintain secure data pipelines, transformations, and analytics infrastructure supporting enterprise systems within a Department of Defense (DoD) modernization initiative. The Data Engineer will ensure accurate, reliable, and performant data flow across applications, integrating structured and unstructured data from multiple mission sources into cloud-based storage and analytics environments. This position plays a critical role in enabling interoperability, analytics, and automation across AWS GovCloud IL2-IL5 environments through the use of scalable data engineering practices and secure DevSecOps integration. This is a fully remote position.\nHere, your work is more than a job - it’s a journey in innovation. With opportunities to work on high-impact projects, access to the latest technologies, and a culture that thrives on creativity and collaboration, INflow Federal is where your expertise can truly make a difference.\nSpecific Duties and Responsibilities:\nDesign, implement, and maintain data pipelines and ETL processes supporting ingestion, transformation, and validation of mission data\nDevelop and optimize data models and schemas across relational and non-relational databases to support system integrations and analytics\nCollaborate with system architects, integration developers, and data analysts to ensure data consistency, security, and integrity across cloud environments\nImplement data migration and synchronization between legacy systems, applications, and modern cloud platforms\nUtilize AWS services (Glue, Lambda, S3, RDS, Redshift, Kinesis) to build and sustain scalable and fault-tolerant data infrastructure\nSupport data validation and reconciliation, performing quality checks and developing reports to ensure accuracy\nIntegrate data from APIs, streaming sources, and file-based systems into centralized repositories or data lakes\nAutomate data workflows using infrastructure-as-code and CI/CD principles to ensure repeatability and efficiency\nMonitor and troubleshoot data pipeline performance, ensuring adherence to SLAs and operational reliability\nImplement data encryption, masking, and access controls in compliance with DoD cybersecurity policies and RMF requirements\nSupport development of dashboards and analytics products, enabling data-driven insights for mission stakeholders\nMaintain documentation and metadata repositories, including data dictionaries, lineage, and technical specifications\nParticipate in Agile sprints, contributing to backlog refinement, testing, and cross-functional collaboration\nRequired Skills:\nProficiency with Python, SQL, and ETL frameworks (e.g., Apache NiFi, Talend, or AWS Glue)\nExperience with cloud data services, preferably AWS GovCloud (RDS, S3, Lambda, Glue, Redshift)\nKnowledge of database management systems (PostgreSQL, SQL Server, DynamoDB, MongoDB)\nFamiliarity with RESTful API integration and data exchange standards (JSON, XML, CSV)\nUnderstanding of DoD data security and compliance standards, including encryption, RMF, and STIG adherence\nExperience developing and maintaining data validation, profiling, and transformation scripts\nExposure to data visualization and analytics tools (Power BI, Tableau, QuickSight)\nFamiliarity with Agile software development and DevSecOps delivery frameworks\nStrong analytical and problem-solving skills for data integration and performance tuning\nExcellent communication and collaboration across technical and functional teams\nAttention to detail with focus on data accuracy and consistency\nAbility to balance data governance, security, and performance objectives\nCommitment to continuous improvement and mission impact through data-driven decision-making\nPreferred certifications: AWS Certified Data Engineer - 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