Closed listing
Senior Azure Databricks Consultant
- Burnaby, BC, Canada
Contract
This opening has closed.
The original listing is kept below for reference.
Job details
- Job type
- Contract
- Closing date
- Posting language
- English
- Posted
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Original job description
Archived listing. The details below describe a past opening.
Position: Senior Azure Databricks Consultant
Location: Burnaby Canada Hybrid
Duration: Long Term Contract
Job Description:
About the Role
We’re seeking an intermediate-level Azure Databricks Engineer to build and optimize scalable data pipelines, manage Delta Lake-based data products, and support analytics/ML workloads. You’ll collaborate with data engineers, analysts, and platform teams to deliver reliable, well-documented, and secure solutions on Azure.
Key Responsibilities
- Design, build, and maintain PySpark/SQL pipelines in Azure Databricks for batch and streaming data.
- Develop robust ingestion from Azure Data Lake Storage (ADLS Gen2), Azure Synapse/SQL, Event Hub, Kafka, and REST/JSON sources.
- Optimize Spark jobs (partitioning, caching, broadcast joins, AQE) for performance and cost.
- Implement monitoring and alerting (cluster/job metrics, driver/executor logs).
- Use Databricks Repos, notebooks, and modular PySpark projects with unit tests (pytest).
- Build CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for jobs, notebooks, and infrastructure-as-code (Terraform/ARM/Bicep).
- Manage environments (dev/test/prod), secrets/Key Vault, and configuration promotion.
Required Qualifications (Intermediate Level)
- 6+ years in data engineering; 4+ years hands-on with Azure Databricks and Spark.
- Strong PySpark and SQL skills: DataFrames, joins, window functions, UDFs, incremental loads.
- Practical experience with Delta Lake, Unity Catalog, and Databricks Jobs/Workflows.
- Familiarity with Azure services: ADLS Gen2, Azure Key Vault, Event Hub, Azure SQL/Synapse.
- Version control (Git) and CI/CD experience; basic testing practices (pytest).
- Ability to optimize Spark jobs and troubleshoot: skew, shuffle, OOM, driver/executor tuning.
- Solid understanding of data modeling (star schema, medallion/lakehouse), partitioning, and file formats (Parquet/JSON).
- Airflow, Azure Data Factory orchestration.
- Terraform for Databricks & Azure resources.
- Basic Scala and/or SQL Warehouses (Databricks SQL) for BI.
Education
- Bachelor’s/Master’s in Computer Science, Engineering, or related field (or equivalent experience).
Certifications (Optional but Valued)
- Databricks: Data Engineer Associate/Professional
- Microsoft Azure: DP-203 (Data Engineering on Microsoft Azure), AZ-900 (Fundamentals)
Tools & Tech Stack (Typical)
- Languages: Python (PySpark), SQL
- Databricks: Notebooks, Jobs/Workflows, Repos, Unity Catalog, Delta Lake, MLflow
- Azure: ADLS Gen2, Key Vault, Event Hub, Synapse/SQL, Monitor/Log Analytics
- DevOps: Git, Azure DevOps/GitHub Actions, Terraform/Bicep
More about this job
Responsibilities
Design, build, and optimize batch and streaming data pipelines in Azure Databricks, integrating data from cloud storage, databases, messaging platforms, and APIs. Maintain Delta Lake data products and support secure, monitored, tested, and CI/CD-managed analytics and machine learning workloads.
Requirements
Requires at least 6 years of data engineering experience, including 4 or more years working hands-on with Azure Databricks and Spark, plus strong PySpark and SQL skills. Candidates should have experience with Delta Lake, Unity Catalog, Azure services, CI/CD, Spark troubleshooting and optimization, data modeling, orchestration, and Terraform; a relevant bachelor's or master's degree or equivalent experience is specified.
Skills
- Azure Databricks
- PySpark
- SQL
- Spark Optimization
- Delta Lake
- Unity Catalog
- Azure Data Lake Storage Gen2
- Azure Synapse
- Azure Event Hubs
- CI/CD
- Git
- Terraform
- Data Modeling
- Airflow
- Azure Data Factory
- pytest
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Consulting
Keywords
- Azure Databricks
- PySpark
- Python
- SQL
- Apache Spark
- Delta Lake
- Unity Catalog
- Databricks Jobs and Workflows
- Databricks Repos
- Azure Data Lake Storage Gen2
- Azure Synapse
- Azure SQL
- Azure Event Hubs
- Kafka
- REST and JSON
- Azure Key Vault
- Azure Monitor
- Log Analytics
- Git
- Azure DevOps
- GitHub Actions
- CI/CD
- Terraform
- Bicep
- pytest
- Airflow
- Azure Data Factory
- Medallion Architecture
- Parquet
- MLflow