12 Aug
|
Benchmark Recruitment
|
Canada
12 Aug
Benchmark Recruitment
Canada
Job Title : Databricks Consultant
12-month contract | Remote in Canada | Closing Date: Wednesday, August 12, 2026 | Must hold a valid Canadian Work Visa
Our client, one of British Columbia's largest organizations dedicated to workplace health and safety, is seeking an experienced Databricks Consultant to lead the design, implementation, and operationalization of an enterprise-scale Databricks platform.
This is a senior consulting role focused on establishing a secure, scalable, and governed Azure Databricks environment that will support enterprise analytics, data engineering, machine learning, and self-service data access. The successful candidate will lead the implementation of Unity Catalog , define platform architecture and governance standards, and work closely with cloud infrastructure, security, data engineering, and business teams to deliver a production-ready data platform.
The ideal candidate brings deep expertise in Databricks platform architecture, data governance, cloud security, and enterprise data engineering, with experience implementing modern Lakehouse solutions in large organizations.
Responsibilities:
Databricks Platform Architecture & Implementation
- Design and implement an enterprise-scale Azure Databricks platform across development, test, and production environments
- Define workspace architecture, environment separation, naming standards, identity models, networking, and workspace lifecycle management
- Configure Databricks account-level administration, workspaces, service principals, security groups, credentials, and access policies
- Establish standards for cluster policies, SQL Warehouses, workflows, repositories, secrets management, and compute governance
- Develop scalable, secure, and cost-effective platform standards that support production operations
Unity Catalog & Data Governance
- Design and implement Unity Catalog as the enterprise governance layer for Databricks
- Define metastore strategies, catalog structures, schema design, naming conventions, ownership models, and environment separation
- Configure catalogs, schemas, tables, views, volumes, storage credentials, external locations, and permissions
- Implement fine-grained access controls using Unity Catalog privileges, service principals, groups, row-level security, column masking, and attribute-based access controls where appropriate
- Enable enterprise capabilities including data discovery, lineage, auditing, data classification, governance, and secure self-service access
Cloud Integration & Platform Security
- Design secure integrations between Databricks and cloud storage platforms, including Azure Data Lake Storage Gen2 (ADLS Gen2)
- Configure managed storage, storage credentials, external locations, and secure access patterns
- Partner with cloud infrastructure and cybersecurity teams to implement private networking, encryption, firewall policies, secrets management, and least-privilege access models
- Ensure platform architecture aligns with enterprise security, privacy, compliance, and governance requirements
Data Engineering Enablement
- Define best practices for Delta Lake, Lakehouse architecture, medallion architecture, batch processing, streaming, and data product development
- Support migration of existing data pipelines, notebooks, workflows, and datasets into Unity Catalog-enabled environments
- Develop reusable templates, standards, implementation guides, and reference architectures for data engineering teams
- Provide technical guidance on schema design, lifecycle management, managed versus external tables, and platform optimization
Operations, Documentation & Knowledge Transfer
- Develop platform documentation, operational procedures, architecture diagrams, and administration runbooks
- Establish operational standards for workspace administration, monitoring, access provisioning, incident response, and cost management
- Define governance roles and responsibilities for platform administrators, data stewards, data owners, engineers, and business users
- Deliver knowledge transfer sessions and mentor internal teams on Databricks platform administration and governance best practices
- Provide recommendations for automation, Infrastructure as Code, CI/CD, observability, and ongoing platform maturity
Qualifications:
Required Qualifications
- Proven hands-on experience implementing and administering Databricks within enterprise environments
- Demonstrated experience designing and implementing Unity Catalog for enterprise data governance
- Robust understanding of Databricks account architecture, workspaces, metastores, catalogs, schemas, tables, views, volumes, storage credentials, external locations, and access controls
- Experience implementing Databricks on cloud platforms, preferably Azure Databricks with ADLS Gen2
- Strong knowledge of data governance, metadata management, data lineage, auditing, access controls, and data classification
- Hands-on experience with Delta Lake , Apache Spark , SQL , Python , notebooks, workflows, and enterprise data engineering pipelines
- Experience with Microsoft Entra ID (Azure AD), SCIM provisioning, service principals, RBAC, and enterprise identity management
- Experience defining cluster policies, SQL Warehouses, compute governance, operational guardrails, and cost optimization strategies
- Strong communication, documentation, consulting, and stakeholder management skills
- Ability to collaborate effectively with cloud infrastructure, cybersecurity, data governance, and engineering teams
Preferred Qualifications
- Databricks Certified Data Engineer Professional certification
- Experience administering enterprise Databricks platforms
- Experience implementing Infrastructure as Code using Terraform , Azure DevOps, GitHub Actions, or CI/CD pipelines
- Experience with Microsoft data platform technologies including Power BI , Microsoft Fabric , Azure Synapse Analytics , Azure Data Factory , and Microsoft Purview
- Experience designing Lakehouse architectures, medallion data models, or enterprise data platform operating models
- Experience implementing enterprise data governance, stewardship, privacy, and compliance frameworks
This is an exciting opportunity to lead the implementation of a modern enterprise Databricks platform that will serve as the foundation for analytics, machine learning, and governed self-service data across the organization. You'll play a key role in shaping data governance, platform architecture, and engineering standards while working with cutting-edge Azure and Databricks technologies. NOTE : Interested candidates who meet the above qualifications are encouraged to apply directly. Due to the volume of applications, only those shortlisted will be contacted.
📌 Databricks Consultant (Canada)
🏢 Benchmark Recruitment
📍 Canada