{"id":2724025,"url":"https://alion.io/job/exavalu-sr-azure-data-architect-databricks","title":"Sr. Azure Data Architect – Databricks","company":{"id":3802017,"name":"Exavalu","domain":"exavalu.com","url":"https://alion.io/company/exavalu","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Dallas, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":123000,"max_usd":246000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":414},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure SQL Database","optional":false},{"name":"Databricks","optional":false},{"name":"Fivetran","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-16T15:50:37Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-10-17T17:25:53Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Overview :\nJob Title: Sr. Data Architect - Azure Databricks\nLocation: REMOTE Hybrid\nKey Responsibilities\nDesign and implement end-to-end data architecture / data ecosystem using Azure-native services and Databricks\nBuild scalable, high-performance data platforms and robust data frameworks\nPartner with stakeholders to translate business requirements into reliable data solutions\nImplement data governance principles using Unity Catalog\nCreate and implement data ingestion and data integration patterns using Medallion Architecture\nApply best practices in data engineering\nDevelop PySpark notebooks\nCreate procedures for advanced data transformation\nHandle performance tuning in Databricks and Azure SQL DBs\nArchitect end-to-end data solutions supporting: \nYield improvement\nProcess control\nPredictive maintenance\nOperational efficiency\n\nEnsure strict governance, security, scalability, and compliance across the platform\nRequired Experience\n10+ years of overall experience and 5+ years of architecture experience in data architecture / data engineering roles\nStrong hands-on experience with major enterprise data platforms\nExtensive experience with Azure-native services including: \nAzure Data Lake Storage (ADLS)\nAzure Data Factory (ADF)\nAzure Synapse Analytics\nAzure SQL\n\nStrong hands-on experience with Azure Databricks\nRequired Databricks Expertise\nShould have worked with the latest Databricks capabilities including:\nUnity Catalog: \nCatalog and schema design\nPermissions and security\nManaged and external tables\nLineage and governance\n\nDelta Live Tables (DLT): \nReliable pipeline development\nCDC implementation\nData transformations\nData quality controls\nScaling and performance tuning\n\nOther modern Databricks capabilities and best practices\nData Ingestion & ELT Experience\nExperience with data ingestion tools such as: \nFivetran\nHVR or equivalent CDC / replication tools\n\nExperience with ELT tools such as: \nDBT\n\nFamiliarity with: \nReal-time / streaming data\nBatch processing\nSensor / OT / ET data flows\n\nRequirements\nTechnical Skills\nStrong expertise in data ingestion, transformation, and orchestration frameworks\nHands-on experience building insurance-specific data models\nProficiency in Python / PySpark and Spark SQL\nStrong understanding of streaming vs batch processing\nExperience with Spark job performance tuning\nAbility to optimize: Data storage formats\nPartitioning strategies\nSchema design\n\nExperience working with: Object stores\nData lakes\nCloud compute scaling\nDatabricks cluster management\n\nGovernance, Security & Operations\nDeep understanding of: Data governance\nSecurity and compliance\nRBAC and attribute-based access control\nEncryption and audit logs\nData privacy requirements\n\nExperience with operational excellence practices: Monitoring and observability\nReliability and metrics\nBackup, failover, and disaster recovery strategies\n\nPreferred Qualifications\nPrior experience working on Insurance P&C cloud-based data and analytics projects\nStrong analytical and problem-solving skills\nExperience defining and enforcing best practices for Databricks workloads and Spark-based pipelines\nSolid understanding of distributed data processing concepts\nStrong communication and stakeholder management skills\nAbility to document architecture decisions, trade-offs, and technical recommendations\nBenefits\nDiversity Inclusion: Exavalu also promotes flexibility, adapting to the needs of employees, customers, and the business. It might be part-time work, working outside normal 9-5 business hours or working remotely. We also offer a welcome back program to help individuals return to the mainstream after a prolonged absence due to health or family reasons. At Exavalu, we are committed to building a diverse and inclusive workforce. We welcome applications for employment from all qualified candidates, regardless of race, colour, gender, national or ethnic origin, age, disability, religion, sexual orientation, gender identity or any other status protected by applicable law. 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