{"id":688944,"url":"https://alion.io/job/fantomcorp-data-engineer","title":"Data Engineer","company":{"id":673180,"name":"Fantom Corporation","domain":"fantomcorp.com","url":"https://alion.io/company/fantomcorp","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":75,"open_postings":12,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["McLean, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":116000,"max_usd":222000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1181},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Airflow","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Docker","optional":false},{"name":"DynamoDB","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Java","optional":false},{"name":"Machine Learning","optional":false},{"name":"MySQL","optional":false},{"name":"NLP","optional":false},{"name":"NumPy","optional":false},{"name":"OCR","optional":false},{"name":"Pandas","optional":false},{"name":"Podman","optional":false},{"name":"PostGIS","optional":false},{"name":"PostgreSQL","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Superset","optional":false},{"name":"Terraform","optional":false},{"name":"Trino","optional":false}],"status":"live","first_seen_at":"2026-07-01T15:43:43Z","employer_posted_date":"2026-07-01","last_verified_at":"2026-10-17T02:30:24Z","board_verified":true,"closed_at":null,"days_open":107,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":107},"description":"Fantom Corporation is a mission-focused organization supporting critical programs across the defense and intelligence community. We partner with our customers to deliver high-impact technical solutions while fostering a culture built on trust, expertise, and long-term career growth.\nWe are seeking a Data & Software Engineer to join a small, agile team developing advanced data solutions for a custom application supporting mission-critical operations. This role is focused on designing, building, and optimizing scalable data pipelines and ETL workflows while leveraging modern cloud technologies, distributed data processing frameworks, and AI/ML capabilities.\nThe ideal candidate has strong Python programming skills, experience building production-grade data pipelines, and expertise with Apache Spark, AWS cloud services, relational databases, and modern data engineering best practices.\nResponsibilities\nDesign, develop, and maintain scalable, end-to-end data pipelines and ETL/ELT workflows supporting enterprise applications\nBuild and optimize distributed data processing solutions using Apache Spark and PySpark\nDevelop robust Python applications and automation scripts to support data engineering initiatives\nDeploy and manage data pipelines using workflow orchestration platforms such as AWS Step Functions or Apache Airflow\nContainerize and deploy data applications within AWS cloud environments using Docker, Podman, or similar technologies\nDesign, optimize, and maintain PostgreSQL and MySQL databases, including schema design, indexing, and query optimization for analytical workloads\nCollaborate with stakeholders to gather requirements, assess technical feasibility, and design scalable data solutions\nTroubleshoot and resolve data quality issues, pipeline failures, and performance bottlenecks\nImplement and support data governance, security, privacy, and compliance best practices\nDevelop and maintain technical documentation, architecture diagrams, and engineering standards\nSupport large-scale data migration and platform modernization initiatives\nIntegrate AI/ML services, machine learning models, and advanced analytics capabilities into enterprise data platforms\nUtilize Git and CI/CD pipelines to support automated testing, deployment, and version control\nRequired Qualifications\nMust be fully cleared with a recent polygraph\n Must be willing and able to work fully onsite at the location listed in this posting\n5+ years of experience as a Data Engineer, Software Engineer, or similar technical role\nDemonstrated experience building production-scale data pipelines and ETL/ELT workflows\nAdvanced programming experience with Python, including libraries such as Pandas and NumPy\nStrong experience with Apache Spark and PySpark for distributed data processing\nExperience with workflow orchestration tools such as Apache Airflow or AWS Step Functions\nExperience deploying containerized applications using Docker, Podman, or similar technologies\nExperience developing cloud-native applications within AWS environments\nHands-on experience with AWS services including Amazon S3, AWS Lambda, and AWS Step Functions\nStrong experience with PostgreSQL and MySQL, including schema design, performance tuning, and query optimization\nAdvanced SQL skills supporting large-scale analytical workloads\nExperience with Git and CI/CD practices for data engineering and software deployment\nUnderstanding of data governance, privacy, security, and compliance principles\nStrong analytical, troubleshooting, and problem-solving skills\nExperience collaborating directly with stakeholders to gather requirements and deliver technical solutions with minimal oversight\n#CJ\nDesired Qualification\nExperience designing and implementing Lakehouse architectures using Apache Iceberg\nExperience configuring and supporting enterprise data platform technologies, including:Apache Ranger\nTrino\nApache Polaris or Unity Catalog OSS\nApache Superset\nExperience with Infrastructure as Code (Terraform or AWS CloudFormation)\nProficiency with Bash scripting for automation and operational support\nExperience tracking data lineage using OpenLineage or similar tools\nWorking knowledge of Java\nExperience implementing data quality frameworks, automated testing, and validation strategies\nExperience supporting enterprise data modernization and large-scale migration initiatives\nExperience integrating AI/ML services, including OCR, NLP, speech-to-text, language detection, translation services, topic modeling, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) pipelines\nExperience processing geospatial data using technologies such as H3, PostGIS, or similar frameworks\nExperience with NoSQL databases such as DynamoDB\nExperience developing engineering standards, documentation, and reusable design patterns","description_format":"text","description_chars":4808,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation"],"lifecycle":[{"event":"open","at":"2026-09-11T00:42:35Z"}],"visa":[],"liveness":{"score":9,"band":"cold","label":"Long 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