We are looking for a Senior Data Engineer to join a rapid-paced, data-driven environment on a contract basis. This role is ideal for an engineer with deep hands-on expertise across the Azure and Databricks ecosystem who can design, build, and optimize enterprise-scale data platforms. You'll play a key role in modernizing ETL/ELT processes, strengthening data governance, and driving cost and performance efficiency across the Databricks Lakehouse.
Key Responsibilities
Design, develop, and maintain scalable ETL/ELT pipelines using Azure and Databricks to support enterprise data and analytics needs
Build and manage Delta Live Tables (DLT) pipelines for reliable, automated data transformation workflows
Implement and maintain Unity Catalog for centralized data governance, access control, and lineage tracking across the Lakehouse
Design and develop semantic layers to support consistent, business-friendly access to curated data for analytics and BI consumption
Build and maintain CI/CD pipelines for data engineering workflows, ensuring automated testing, deployment, and version control best practices
Own FinOps practices within Databricks — monitoring, forecasting, and optimizing compute/storage costs across clusters and jobs
Conduct performance tuning and optimization of Databricks workloads, including cluster configuration, query optimization, and job orchestration
Work across core Azure data services (e.g., Azure Data Factory, Azure Data Lake Storage, Azure Synapse) to integrate and orchestrate data pipelines
Partner with data architects, analysts, and business stakeholders to translate requirements into robust, scalable data solutions




Ensure data quality, security, and compliance standards are upheld across all pipelines and platforms
Troubleshoot and resolve pipeline failures, performance bottlenecks, and data quality issues in a timely manner
Required Skills & Experience
Proven experience as a Senior Data Engineer, with a strong track record delivering production-grade data pipelines
Strong hands-on experience with Microsoft Azure (Azure Data Factory, ADLS, Azure Synapse, or similar)
Deep expertise in Databricks , including:
Unity Catalog
Cluster and job performance optimization
FinOps / cost management within Databricks
Strong experience building and maintaining CI/CD pipelines for data engineering workflows (e.g., Azure DevOps, GitHub Actions)
Experience designing and implementing semantic layers for analytics/BI consumption
Solid background in ETL/ELT pipeline design, development, and optimization
Proficiency in Python and/or SQL for data transformation and pipeline development
Strong understanding of data governance, security, and lineage best practices
Excellent problem-solving skills and ability to work independently in a contract setting
Strong communication skills, with the ability to work cross-functionally with technical and business stakeholders
Nice to Have
Databricks certifications (e.g., Databricks Certified Data Engineer Professional)
Experience with Terraform or other infrastructure-as-code tools in an Azure/Databricks context
Experience in a regulated or enterprise-scale industry
Familiarity with Spark internals and advanced performance tuning

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📌 Senior Data Engineer (Ontario)
🏢 Xinova Group
📍 Ontario