{"id":2673397,"url":"https://alion.io/job/ltm-associate-principal-data-engineering-2","title":"Associate Principal - Data Engineering","company":{"id":9353,"name":"Ltm","domain":"ltm.com","url":"https://alion.io/company/ltm","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":75,"open_postings":137,"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":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mumbai, 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platforms using the Databricks Lakehouse architecture\nDefine endtoend data architecture including ingestion transformation storage governance and consumption layers\nEstablish architectural standards framework guidelines coding best practices and reusable design patterns\nLead technical decisions related to scalability performance optimization reliability and security\nConduct architecture reviews and provide recommendations to project teams\nData Engineering Databricks Implementation\nDesign and build scalable ETLELT pipelines using PySpark on Databricks\nArchitect and implement Bronze Silver Gold data transformation frameworks\nDesign and manage Delta Lake based storage architecture including partitioning optimization and data lifecycle management\nImplement Databricks Lakeflow pipelines for data orchestration and automation\nDefine data quality validation reconciliation and monitoring frameworks\nOversee CICD and DevOps practices for data engineering projects\nData Modeling Analytics Enablement\nDesign and implement enterprise data models using Dimensional Modeling techniques\nDevelop Star Schemas Fact Tables Dimension Tables and conformed dimensions\nDefine business metrics KPI layers and semantic models\nArchitect and implement Metric Views and curated Gold datasets for reporting and analytics\nWork closely with business stakeholders to translate requirements into scalable analytical models\nTechnical Leadership\nProvide technical leadership and mentorship to data engineers and developers\nPerform code reviews and ensure adherence to architecture standards\nTroubleshoot complex technical issues and guide teams in solution design\nSupport estimation solution proposals and technical governance activities\nDrive adoption of modern data engineering and cloudnative best practices\nRequired Technical Skills\nCore Databricks Skills\nDatabricks Lakehouse Architecture\nDatabricks Workflows Lakeflow\nDelta Lake\nUnity Catalog\nDatabricks SQL\nPerformance Tuning Optimization\nData Engineering\nPySpark\nSpark SQL\nETL ELT Design\nData Pipeline Development\nData Quality Frameworks\nBatch and Incremental Processing\nData Modeling\nDimensional Data Modeling\nStar Schema Design\nFact Dimension Modeling\nSlowly Changing Dimensions SCD\nMetric View Design\nAnalytical Data Modeling\nCloud Integration\nAzure Databricks preferred\nADLS Gen2\nAzure Data Factory ADF\nEventbased and Batch Ingestion Patterns\nData Governance and Security\nProgramming\nPython\nSQL\nGit\nCICD Frameworks\nDesired Skills\nData Warehouse Modernization experience\nExperience migrating legacy EDW solutions to Databricks\nExposure to Data Mesh and Medallion Architecture\nKnowledge of Data Governance Metadata Management and Data Cataloging\nExperience supporting BI platforms such as Power BI Tableau or Looker\nLeadership Expectations\nThe candidate should be capable of\nOwning the complete Databricks implementation lifecycle\nDefining targetstate architecture and roadmap\nReviewing 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