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Galent

Senior Databricks Data Platform Engineer

Montreal, QC, Canada

Contract

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Job details

Job type: Contract
Apply by: Dec 2, 2026
Posting language: English
Posted: Nov 2, 2026

Original job description

Job Title: Senior Databricks Data Platform Engineer

Location: Montreal, QC

Job Description:

Databricks Platform Engineering Administration

Own the architecture configuration and lifecycle Databricks environments across development test and production including workspaces account level settings networking and identity integration
Administer and evolve Unity Catalog including metastores catalogs schema's external locations storage credentials and fine-grained access controls
Design and enforce compute strategy across all-purpose clusters job clusters serverless compute SQL warehouses instance pools and cluster policies
Manage platform upgrades Databricks Runtime adoption feature previews and deprecations with minimal disruption to consuming teams
Build reusable platform templates starter projects and self-service capabilities that let engineering teams onboard quickly and consistently

CICD Platform Automation

Design build and maintain CICD pipelines for Databricks code and configuration using Databricks Asset Bundles Git folders and Azure DevOps or GitHub Actions
Codify platform infrastructure with Terraform Databricks and cloud providers ensuring every workspace cluster policy permission and Unity Catalog object is version controlled and reproducible
Implement automated testing code quality gates security scanning and promotion workflows from development through production
Establish branching release and rollback standards for notebooks jobs Delta Live Tables Lake flow pipelines and ML assets
Automate routine administration such as user and group provisioning SCIM secret management token rotation and environment drift detection

Agentic Workflows AI Enabled Operations

Design and deploy agentic workflows that automate platform operations such as job failure triage root cause analysis cost anomaly investigation and remediation recommendations
Build AI agents and tools on Databricks Mosaic AI Agent Framework Model Serving Vector Search and integrate them with enterprise systems through Model Context Protocol MCP
Use Copilot and Anthropic models to accelerate infrastructure as code pipeline development code review and documentation
Establish guardrails evaluation observability and human in the loop controls so agentic automation is safe auditable and trusted
Partner with data science and engineering teams to provide a governed platform foundation for GenAI RAG and ML workloads

Platform Cost Optimization FinOps

Own Databricks cost visibility and accountability using system tables billing usage compute and query history tagging standards and chargeback or show back reporting
Identify and deliver savings through cluster rightsizing auto termination autoscaling tuning spot and reserved capacity strategies Photon and serverless evaluation and workload consolidation
Enforce cost guardrails through cluster policies budget s and compute governance that prevent waste without slowing teams down
Build dashboards and automated s that surface cost anomalies idle resources and optimization opportunities to engineering and finance stakeholders
Partner with finance and procurement on DBU commitments forecasting and capacity planning

Storage Performance Optimization

Define and enforce Delta Lake storage standards including file sizing liquid clustering Zordering partitioning strategy and deletion vectors
Automate table maintenance using predictive optimization OPTIMIZE VACUUM and retention policies to control storage growth and improve query

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, citizenship status, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable law. https://www.e-verify.gov/sites/default/files/everify/posters/IER_RighttoWorkPoster.pdf

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More about this job

Responsibilities

Own and evolve Databricks environments, Unity Catalog, compute, infrastructure automation, CI/CD, and platform operations across development, test, and production. Improve platform reliability, security, cost efficiency, and storage performance while enabling governed AI, machine learning, and data engineering workloads.

Requirements

The role calls for mid-to-senior-level expertise in Databricks platform engineering, infrastructure as code, CI/CD, cloud administration, and data platform governance. It also involves cost optimization, Delta Lake performance practices, and building safe, observable AI-enabled operational workflows; no specific education requirement is stated.

Skills

Unity Catalog
Terraform
CI/CD
Azure DevOps
GitHub Actions
Databricks Asset Bundles
Agentic Workflows
Mosaic AI
Model Serving
Vector Search
Model Context Protocol
FinOps
Delta Lake
Cloud Infrastructure
Platform Automation

Visa sponsorship

Not detected in the job text

Keywords

Databricks
Unity Catalog
Terraform
Azure DevOps
GitHub Actions
Databricks Asset Bundles
CI/CD
SCIM
Delta Lake
Delta Live Tables
Mosaic AI Agent Framework
Model Serving
Vector Search
Model Context Protocol
Anthropic Models
Copilot
FinOps
Photon
Serverless Compute
SQL Warehouses
Cluster Policies
System Tables
Predictive Optimization
OPTIMIZE
VACUUM
Infrastructure as Code
Agentic Workflows
Root Cause Analysis
Cost Optimization
Access Controls

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