{"id":3751180,"url":"https://alion.io/job/link-group-snowflake-data-engineer-airflow","title":"Snowflake Data Engineer (Airflow)","company":{"id":880,"name":"Link Group","domain":"linkgroup.co","url":"https://alion.io/company/link-group","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":"Recruitify","truth_index":{"grade":"B","score":82,"open_postings":92,"ghost_share":0,"stale_share":0.739,"repost_share":0,"time_to_fill_p50_days":44,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Data Science","role_family":"Data 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Expectations","optional":true},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-10-23T00:00:00Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-11-07T09:31:27Z","board_verified":true,"closed_at":null,"days_open":15,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":15},"description":"Snowflake Data Engineer (Airflow)\nResponsibilities\nDevelop and maintain data pipelines using Apache Airflow and Python.\nBuild data ingestion processes from APIs, databases, and file-based sources into AWS S3 and Snowflake.\nDesign and implement data transformations using dbt.\nOptimize Snowflake queries, warehouse performance, and resource consumption.\nImplement pipeline monitoring, error handling, and alerting mechanisms.\nEnsure data quality, consistency, and reliability through automated testing and validation.\nMaintain technical documentation and follow data engineering best practices.\nRequirements\n3+ years of professional experience in Data Engineering.\nStrong expertise in Apache Airflow, including DAG development, operators, sensors, hooks, TaskFlow API, and workflow optimization.\nAdvanced Python skills, including writing clean, maintainable, and testable code.\nAdvanced SQL knowledge, including complex queries, CTEs, window functions, and performance optimization.\nHands-on experience with Snowflake, including warehouses, stages, external volumes, and data loading processes.\nPractical knowledge of dbt, including models, tests, macros, snapshots, and incremental transformations.\nExperience with AWS S3 and Data Lake architecture, including data partitioning, file formats, and access management.\nFamiliarity with Git and CI/CD practices.\nEnglish proficiency at B2 level or higher.\nNice to Have\nExperience with Docker and Kubernetes.\nKnowledge of Apache Iceberg or Delta Lake.\nFamiliarity with data quality and observability tools such as Great Expectations or Soda.\nUnderstanding of dimensional data modeling 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