{"id":3627759,"url":"https://alion.io/job/element-solutions-data-engineer","title":"Data Engineer","company":{"id":4407906,"name":"Element Solutions","domain":"elementsolutions.io","url":"https://alion.io/company/element-solutions","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":95000,"max":106000,"currency":"USD","period":"year","gross":null,"usd_annual":106000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"CI/CD","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Rest API","optional":true}],"status":"live","first_seen_at":"2026-10-28T20:47:32Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-11-04T05:24:53Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"Who is Element?\nWe serve as a partner at the intersection of innovation and our clients' needs, efficiently crafting meaningful user experiences for government and commercial customers. By breaking complex problems down into their fundamental elements, we create modern digital solutions that drive efficiency, maximize taxpayer dollars, and deliver essential outcomes that serve the people.\nWhy Work at Element?\nMake an impact that resonates-join our vibrant team and discover how you can improve lives through digital transformation. Our talented professionals bring unparalleled energy and engagement, setting a higher standard for impactful work. Be a part of our team and shape a better future.\nPosition Summary\nElement Solutions is looking for an analytical and critical thinking Data Engineer. The Data Engineer is responsible for designing, developing, implementing, and maintaining scalable data pipelines and data solutions that support customer and organizational needs. This role leverages Snowflake and Apache Airflow to build and manage data integration workflows, optimize data processing, and ensure data quality, reliability, and accessibility.\nThe Data Engineer works collaboratively with senior engineers, software developers, data analysts, and other project stakeholders to translate technical and business requirements into effective data solutions. This position requires hands-on experience with cloud-based data platforms, workflow orchestration, SQL development, automation, and data pipeline monitoring. The ideal candidate can independently manage routine engineering tasks, troubleshoot technical issues, and contribute to the continuous improvement of data infrastructure and engineering practices.\nKey Responsibilities\nData Pipeline Development and Management\nDesign, build, and maintain reliable, scalable ETL/ELT pipelines for ingesting, transforming, and delivering data.\n\nDevelop Apache Airflow DAGs to orchestrate pipeline tasks, schedules, dependencies, and data-processing workflows.\n\nIntegrate data from sources such as databases, APIs, and files, applying appropriate transformations and preserving data consistency.\n\nDevelop SQL transformations and Snowflake data structures to support downstream data use.\n\nBuild reusable pipeline components and automate recurring processes to improve maintainability and reduce manual effort.\n\nSupport pipeline configuration and deployments across development, test, and production environments.\n\nSnowflake Development and Optimization\nDevelop and maintain Snowflake database objects, including schemas, tables, and views.\n\nImplement data loading and transformation processes using Snowflake capabilities and the organization’s approved integration tools.\n\nOptimize SQL queries and Snowflake workloads by evaluating query performance, warehouse sizing and utilization, and cost.\n\nApply appropriate Snowflake data modeling and performance optimization techniques, including clustering when beneficial for the workload.\n\nImplement and maintain Snowflake roles and permissions in accordance with organizational and customer security requirements.\n\nWorkflow Orchestration and Automation\nConfigure Airflow schedules, task dependencies, retries, timeouts, and failure handling to support reliable data workflows.\n\nMonitor workflow runs, investigate failures, and implement corrective actions to prevent recurring issues.\n\nConfigure alerts and operational logging to support timely detection and troubleshooting of pipeline issues.\n\nDevelop Python scripts and automation to support pipeline operations; use SQL where appropriate for data transformations.\n\nMaintain workflow and operational documentation, including dependencies, recovery steps, and troubleshooting guidance.\n\nData Quality, Testing, and Security\nDevelop and maintain automated data validation checks and tests to assess accuracy, completeness, consistency, and integrity.\n\nInvestigate and resolve data-quality issues, documenting their causes and corrective actions.\n\nFollow established data governance, privacy, security, and access-management requirements when handling data.\n\nDocument data lineage and transformation logic to support traceability and maintainability.\n\nFollow established procedures for error handling and data recovery, and support compliance with applicable customer, organizational, and regulatory requirements.\n\nCollaboration and Continuous Improvement\nWork with technical teams and stakeholders to clarify data requirements and deliver practical engineering solutions.\n\nParticipate in code reviews, technical design discussions, and development planning.\n\nContribute to shared engineering practices for version control, automated testing, and CI/CD.\n\nIdentify and propose improvements to the reliability, scalability, maintainability, and cost efficiency of data solutions.\n\nShare knowledge with teammates and provide technical guidance when appropriate.\n\nPerform other related duties as assigned.\n\nMinimum Requirements\nBachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or Associates degree plus two years' experience.\n\nAt least 3 years of professional experience in data engineering, data integration, ETL/ELT development, or a related technical field.\n\nAt least 3 years of hands-on experience with Snowflake and Apache Airflow in data engineering or data pipeline development.\n\nStrong proficiency in SQL, including query development, data transformation, and performance optimization.\n\nExperience developing, scheduling, monitoring, and troubleshooting data pipelines using Apache Airflow.\n\nExperience designing and maintaining data structures, transformations, and workflows in Snowflake.\n\nProficiency in Python or a comparable scripting language for automation and data processing.\n\nUnderstanding of relational databases, data modeling, data integration patterns, and data quality practices.\n\nExperience with version control tools such as Git and collaborative software development practices.\n\nStrong analytical, troubleshooting, and problem-solving skills.\n\nAbility to work independently on assigned engineering tasks while collaborating effectively with technical teams and stakeholders.\n\nMust live in the Continental US.\n\nBe either a US citizen or Permanent Resident due to the work we do.\n\nDepending on agency requirements, you may need to possess or obtain a Public Trust designation or security clearance. Regardless of the specific requirement, all positions require the successful completion of a background check, background investigation, and the standard onboarding process.\n\nPreferred Qualifications\nExperience supporting data engineering solutions in a government contracting, healthcare CMS (Center of Medicare & Medicaid) or in the health industry, or other regulated environment.\n\nExperience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.\n\nFamiliarity with cloud-based storage services and data ingestion tools.\n\nExperience implementing CI/CD pipelines and automated testing for data workflows.\n\nKnowledge of data governance, data lineage, metadata management, and role-based access controls.\n\nExperience working with REST APIs, JSON, and other structured or semi-structured data formats.\n\nFamiliarity with containerization technologies such as Docker.\n\nQualified individuals living in HUBZone-certified areas are strongly encouraged to apply. 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