{"id":2086432,"url":"https://alion.io/job/ascendion-senior-data-engineer","title":"Senior Data Engineer","company":{"id":46972,"name":"Ascendion","domain":"ascendion.com","url":"https://alion.io/company/ascendion","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"B","score":81,"open_postings":33,"ghost_share":0,"stale_share":0.758,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-10-09T06:01:00Z"}},"role":"Data Science","role_family":"Data 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Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-08T09:48:05Z","employer_posted_date":"2026-10-08","last_verified_at":"2026-10-09T23:33:00Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Key Responsibility Areas:\nDesign and develop scalable, secure, and high-performance data engineering solutions on Microsoft Azure.\nArchitect and implement complex ETL/ELT data pipelines using Azure Data Factory and Azure Databricks.\nDevelop highly optimized PySpark applications and Databricks notebooks for large-scale data processing.\nDesign and implement batch and incremental data processing frameworks.\nDevelop complex SQL queries, stored procedures, CTEs, window functions, and data transformations.\nDesign and implement data ingestion solutions from multiple structured and semi-structured data sources.\nWork extensively with Azure Data Lake Storage Gen2, Delta Lake, and Parquet.\nDesign and implement Medallion Architecture (Bronze, Silver, Gold) and modern data lake/lakehouse solutions.\nOptimize Databricks clusters, Spark jobs, PySpark code, SQL queries, and data pipelines for performance and cost.\nDevelop robust error handling, logging, monitoring, and data validation mechanisms.\nImplement data quality, reconciliation, and validation frameworks.\nTroubleshoot complex production issues and provide root-cause analysis and permanent solutions.\nLead technical discussions and contribute to data architecture and solution design.\nMentor junior and mid-level data engineers and provide technical guidance.\nCollaborate with Data Architects, Developers, Data Scientists, Business Analysts, and other stakeholders.\nParticipate in code reviews and establish engineering best practices and coding standards.\nImplement CI/CD processes for data engineering workloads using Azure DevOps/Git.\nEnsure solutions comply with organizational standards for security, governance, scalability, and reliability.\nMandatory Technical Skills\n7-11 years of overall experience in Data Engineering / Data Platforms.\nStrong hands-on experience with Azure Databricks.\nStrong experience with Azure Data Factory (ADF).\nExcellent hands-on experience with PySpark and Python.\nAdvanced proficiency in SQL.\nStrong understanding of Apache Spark and distributed data processing.\nExperience with Delta Lake and Parquet.\nStrong experience designing and developing ETL/ELT pipelines.\nStrong understanding of data warehousing and data modeling concepts.\nExperience with Azure Data Lake Storage Gen2 (ADLS Gen2).\nExperience with performance tuning and optimization of Spark/PySpark workloads.\nExperience with production support, troubleshooting, monitoring, and data pipeline 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