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Added 11 mins ago
Consultant en Déploiement - Apprentissage automatique | Delivery Consultant - Machine Learning, ProServe Shared Delivery Team - Data & AI
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Calgary, AB · Vancouver, BC · Toronto, ON · Montreal, QC
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Azure Cloud Engineer - Senior Consultant
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Senior Software Engineer
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Azure Cloud Platform Engineer + ADF
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Platform Engineer - Depop
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Added 2 hours ago
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Senior Corrugated Reliability Engineer
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The Senior Corrugated Reliability Engineer with a Six Sigma certification combines machine uptime, root-cause failure analysis, and data-driven process control to eliminate defects and…
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Added 2 hours ago
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Lead Software Engineer
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Enterprise Solutions Inc.

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

Title: Senior Databricks Data Platform Engineer

Location: Montreal, QC (Hybrid)

Type: Contract

Job description

Role Overview

As a Senior Databricks Data Platform Engineer you will own the engineering automation and day to day health of our enterprise Databricks Lakehouse platform This is a platform-first role rather than building individual business pipelines you will build the foundation that every data engineer analyst and data scientist at Client depends on including workspaces compute Unity Catalog governance deployment pipelines and the guardrails that keep the platform secure reliable and cost-efficient
You will treat the platform as a product That means codifying infrastructure and configuration delivering changes through fully automated CICD introducing agentic AI workflows that reduce manual operational effort and continuously driving down compute and storage cost while improving performance You will combine deep hands-on Databricks expertise with a FinOps and DevOps mindset and you will measure your success in platform reliability developer productivity and dollars saved
This is a highly collaborative role You will partner with data engineering data science security cloud infrastructure and finance teams to set platform standards, guide adoption of new Databricks capabilities and mentor engineers across the organization

About the role

Databricks Platform Engineering Administration
Own the architecture configuration and lifecycle of Client Databricks environments across development test and production, including workspaces, account-level settings, networking and identity integration
Administer and evolve Unity Catalog including metastores catalogs schemas, 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, Lakeflow 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 rootcause 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 showback 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

Skills

Mandatory Skills : Databricks

Good to Have Skills : Azure Databricks

We are an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees

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More about this job

Responsibilities

Own the architecture, administration, automation, security, and lifecycle of the enterprise Databricks Lakehouse platform across development, test, and production environments. Build CI/CD and agentic operational workflows, govern compute and storage, and optimize platform reliability, developer productivity, and costs in collaboration with engineering, security, infrastructure, data science, and finance teams.

Requirements

The role calls for senior-level, hands-on Databricks platform engineering expertise, including Unity Catalog, compute governance, infrastructure as code, and automated deployment practices. It also emphasizes DevOps and FinOps capabilities, cost and performance optimization, and experience applying AI agents and operational guardrails to platform workflows.

Skills

Databricks
Azure Databricks
Unity Catalog
Terraform
CI/CD
Azure DevOps
GitHub Actions
Databricks Asset Bundles
Mosaic AI Agent Framework
Model Serving
Vector Search
Model Context Protocol
FinOps
Delta Lake
Lakeflow
Cloud Platform Engineering

Visa sponsorship

Not detected in the job text

Keywords

Databricks
Azure Databricks
Lakehouse
Unity Catalog
Terraform
Databricks Asset Bundles
Azure DevOps
GitHub Actions
CI/CD
Infrastructure As Code
Mosaic AI Agent Framework
Model Serving
Vector Search
Model Context Protocol
Copilot
Anthropic Models
FinOps
DevOps
Delta Lake
Lakeflow
Delta Live Tables
Serverless Compute
Cluster Policies
SCIM
Predictive Optimization
Photon
Cost Anomaly Detection
Platform Engineering
Cloud Infrastructure
GenAI

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