{"id":3908248,"url":"https://alion.io/job/querentia-senior-data-engineer-databricks-microsoft-fabric","title":"Senior Data Engineer – Databricks & Microsoft Fabric","company":{"id":4460938,"name":"Querentia","domain":"querentia.com","url":"https://alion.io/company/querentia","size_band":"1-10","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":{"grade":"C","score":57,"open_postings":218,"ghost_share":0.716,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-09T06:03:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"contractor","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","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":"Git","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Rest API","optional":true}],"status":"live","first_seen_at":"2026-10-21T00:00:00Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-11-08T00:21:07Z","board_verified":true,"closed_at":null,"days_open":19,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":19},"description":"Senior Data Engineer - Databricks & Microsoft FabricWork Location: Toronto, Canada\nJob Summary\nWe are seeking a Senior Data Engineer with strong expertise in Azure Databricks and modern cloud data platforms to design, develop, and optimize scalable data pipelines, lakehouse solutions, and analytics platforms. The role focuses primarily on Databricks data engineering, with additional experience in Microsoft Fabric and Databricks Genie to support self-service analytics, conversational AI, and enterprise reporting.\nKey Responsibilities\nDesign, develop, and maintain scalable ETL/ELT pipelines using Azure Databricks, PySpark, Spark SQL, and Delta Lake.\nImplement Medallion Architecture (Bronze, Silver, Gold) and integrate data from APIs, databases, files, ERP, CRM, and cloud storage.\nOptimize Spark jobs, cluster configurations, and data processing workloads for performance and cost efficiency.\nDevelop reusable frameworks for data ingestion, transformation, and quality validation.\nImplement CI/CD pipelines using Azure DevOps or Git-based deployment practices.\nMonitor and troubleshoot production data pipelines.\nDevelop data solutions using Microsoft Fabric components, including Data Factory, Lakehouse, Warehouse, Notebooks, and Data Pipelines.\nSupport data modernization initiatives, Power BI semantic models, and enterprise reporting solutions.\nSupport Databricks Genie implementation, semantic layer development, and natural language querying for self-service analytics.\nApply data governance, security, and access controls across data platforms.\nCollaborate with business analysts, architects, and stakeholders to translate business requirements into technical solutions.\nRequired Qualifications\nBachelor's degree in Computer Science, Engineering, Information Technology, or a related field.\n7+ years of experience in data engineering.\n4+ years of hands-on experience with Azure Databricks.\nStrong proficiency in PySpark, Spark SQL, Python, SQL, and Delta Lake.\nExperience with Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), and Git/Azure DevOps.\nStrong understanding of ETL/ELT development, data modeling, data warehousing, and performance optimization.\nExperience designing and delivering enterprise cloud data platforms.\nExperience developing scalable data pipelines and implementing data quality practices.\nNice to Have\nExperience with Microsoft Fabric, including Lakehouse, Warehouse, Data Factory, Notebooks, and Data Pipelines.\nFamiliarity with Power BI and semantic model development.\nExperience with Databricks Genie and AI-powered conversational analytics.\nKnowledge of Unity Catalog, Databricks Workflows, REST APIs, and data governance.\nExperience with AI/GenAI-enabled analytics solutions.\nDatabricks Associate or Professional 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