Posted 17 days ago
Senior Data Engineer – Databricks & Microsoft Fabric
@ Querentia Inc.
Toronto, Ontario
Overview
Querentia Inc. is hiring a Senior Data Engineer on a contract basis in Toronto to design and optimize scalable pipelines and lakehouse solutions. The role centres on Azure Databricks with additional Microsoft Fabric and Databricks Genie work.
Responsibilities:
- Design and maintain ETL/ELT pipelines on Azure Databricks
- Implement Medallion Architecture and integrate diverse data sources
- Optimize Spark jobs and cluster configurations
- Develop Microsoft Fabric solutions and support Power BI reporting
- Implement CI/CD pipelines and monitor production data pipelines
Requirements summary:
- Bachelor's degree in computer science, engineering or IT
- 7+ years in data engineering, 4+ years with Azure Databricks
- Proficiency in PySpark, Spark SQL, Python, SQL and Delta Lake
- Experience with ADLS, ADF and Git/Azure DevOps
- Experience with Microsoft Fabric and Databricks Genie preferred
Tools & skills
Source and dates
Source type not verified · jsonld
- Employer posting date
- 2026-10-20
- First seen by our source
- 2026-10-26
- Source record updated
- 2026-11-05
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Software development |
| Experience | 7+ years |
| Travel | air: none · ground: none |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Education | Bachelor’s degree (required) |
| Fields of study | Computer Science, Engineering, Information Technology |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Querentia Inc.
| Field | Value |
|---|---|
| Open jobs on Jobsy | 331 |
Senior Data Engineer - Databricks & Microsoft Fabric
Work Location: Toronto, Canada
Job Summary
We 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.
Key Responsibilities
•
Design, develop, and maintain scalable ETL/ELT pipelines using Azure Databricks, PySpark, Spark SQL, and Delta Lake.
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Implement Medallion Architecture (Bronze, Silver, Gold) and integrate data from APIs, databases, files, ERP, CRM, and cloud storage.
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Optimize Spark jobs, cluster configurations, and data processing workloads for performance and cost efficiency.
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Develop reusable frameworks for data ingestion, transformation, and quality validation.
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Implement CI/CD pipelines using Azure DevOps or Git-based deployment practices.
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Monitor and troubleshoot production data pipelines.
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Develop data solutions using Microsoft Fabric components, including Data Factory, Lakehouse, Warehouse, Notebooks, and Data Pipelines.
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Support data modernization initiatives, Power BI semantic models, and enterprise reporting solutions.
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Support Databricks Genie implementation, semantic layer development, and natural language querying for self-service analytics.
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Apply data governance, security, and access controls across data platforms.
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Collaborate with business analysts, architects, and stakeholders to translate business requirements into technical solutions.
Required Qualifications
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Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.
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7+ years of experience in data engineering.
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4+ years of hands-on experience with Azure Databricks.
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Strong proficiency in PySpark, Spark SQL, Python, SQL, and Delta Lake.
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Experience with Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), and Git/Azure DevOps.
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Strong understanding of ETL/ELT development, data modeling, data warehousing, and performance optimization.
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Experience designing and delivering enterprise cloud data platforms.
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Experience developing scalable data pipelines and implementing data quality practices.
Nice to Have
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Experience with Microsoft Fabric, including Lakehouse, Warehouse, Data Factory, Notebooks, and Data Pipelines.
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Familiarity with Power BI and semantic model development.
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Experience with Databricks Genie and AI-powered conversational analytics.
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Knowledge of Unity Catalog, Databricks Workflows, REST APIs, and data governance.
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Experience with AI/GenAI-enabled analytics solutions.
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Databricks Associate or Professional certification.
Journal
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