{"id":1621308,"url":"https://alion.io/job/exl-senior-azure-databricks-data-engineer","title":"Senior Azure Databricks Data Engineer","company":{"id":38016,"name":"EXL","domain":"exlservice.com","url":"https://alion.io/company/exl","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":80,"open_postings":62,"ghost_share":0,"stale_share":0.984,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-10-07T05:47:15Z"}},"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":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":120000,"max_usd":233000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":960},"experience_years_min":9,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Machine Learning","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Agile","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Master Data Management","optional":true},{"name":"Microsoft Fabric","optional":true},{"name":"Power BI","optional":true},{"name":"Scrum","optional":true},{"name":"Snowflake","optional":true}],"status":"live","first_seen_at":"2026-09-24T19:02:40Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-10-08T02:32:18Z","board_verified":true,"closed_at":null,"days_open":13,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":13},"description":"Job Summary\nWe are seeking a skilled Databricks Engineer with minimum of 5+ years of hands-on in Databricks who can design, develop, and optimize scalable data platforms and analytics solutions using the Databricks Lakehouse Platform. The ideal candidate will have expertise in data engineering, ETL/ELT development, cloud technologies preferably Azure, and big data processing to support enterprise analytics and AI initiatives.\nJob Description: Azure / Databricks Data Engineer (9-15 Years Experience)\nSenior Azure Databricks Data Engineer\nExperience\n9-15 Years of IT Experience\nLocation\nHybrid\nJob Summary\nWe are seeking a skilled Databricks Engineer withminimum of 5+ years of hands-on in Databricks who can design, develop, and optimize scalable data platforms and analytics solutions using the Databricks Lakehouse Platform. The ideal candidate will have expertise in data engineering, ETL/ELT development, cloud technologies preferably Azure, and big data processing to support enterprise analytics and AI initiatives.\nKey Responsibilities\nDesign, develop, and maintain data pipelines using Databricks, Apache Spark, and cloud-native services.\nBuild and optimize ETL/ELT workflows for large-scale structured and unstructured data.\nDevelop data models and implement data quality, validation, and governance frameworks.\nIntegrate data from multiple sources into a unified Lakehouse architecture.\nOptimize Spark jobs and Databricks workloads for performance, scalability, and cost efficiency.\nImplement security controls, access management, and data governance using Unity Catalog.\nCollaborate with business, analytics, and AI/ML teams to deliver trusted data products.\nMonitor, troubleshoot, and resolve data pipeline issues.\nSupport CI/CD, DevOps, and infrastructure automation practices.\nMaintain technical documentation and best practices.\nRequired Technical Skills Core Technologies\nDatabricks Lakehouse Platform\nApache Spark / PySpark\nDelta Lake\nSQL\nPython\nData Engineering\nETL / ELT Development\nData Modeling\nData Warehousing\nData Quality & Validation\nStreaming & Real-Time Processing\nGovernance & Security\nUnity Catalog\nData Lineage\nRow-Level Security\nAccess Control & Compliance\nData Governance Frameworks\nCloud & DevOps\nAzure / AWS / GCP\nTerraform\nGitHub Actions / Azure DevOps\nCI/CD Pipelines\nAnalytics & AI\nSemantic Layers\nData Products\nBI Platforms\nMachine Learning Support\nGenerative AI & RAG Architectures\nRequired Qualifications\nBachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field.\n9-15 years of experience in Data Engineering and Data Warehousing.\nMinimum 5+ years of hands-on experience with Azure Data Engineering technologies.\nMinimum 4+ years of hands-on experience with Azure Databricks and Spark ecosystem.\nStrong understanding of data lake, lakehouse, and cloud-native architecture patterns.\nExperience in handling large-scale structured and unstructured datasets.\nStrong analytical, problem-solving, and troubleshooting skills.\nPreferred Qualifications\nMicrosoft Certified: Azure Data Engineer Associate (DP-203).\nDatabricks Certified Data Engineer Associate/Professional.\nExperience with Snowflake, Power BI, or Microsoft Fabric.\nExperience in real-time streaming solutions using Kafka/Event Hubs.\nExposure to Data Governance and Master Data Management initiatives.\nSoft Skills\nStrong stakeholder management and communication skills.\nAbility to lead technical initiatives and drive architecture discussions.\nExperience working in Agile/Scrum environments.\nExcellent documentation and presentation skills.\nStrong mentoring and team leadership abilities.\nNice to Have\nMicrosoft Fabric\nPower BI\nAzure Event Hubs\nKafka\nMachine Learning data pipelines\nData Governance tools such as Purview\nSupport critical and nonproduction databases in multitenant, highstress environments.Support applications Installation, Configuration, Management, and Monitoring of databases in a SOX and PHI compliant environment\nInstallation, configuration, and integration of thirdparty applications and tools\nDevelopment of procedures for automated monitoring and proactive intervention, preventing customer impact Bachelors Degree/ Post Bachelor Degree 8 - 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