Find work in Canada.

622,832 jobs across our Canadian network. How we count

Jobs in Canada

Email me new jobs Save this search

Added 2 days ago
A(
Machine Learning Resident - Client: ModeDi (12 month term)
Amii (Alberta Machine Intelligence Institute)
AB · Edmonton, AB
- Full-time
This is a paid Residency that will be undertaken over a twelve-month period with the potential to be hired by our client, ModeDi, afterwards (note: at the discretion of the client). The…
Added 2 days ago
VS
Data Science Developer
vTech Solution Canada
Toronto, ON
- Contract
Strong programming skills, particularly Python and SQL, with experience developing production-quality applications.
Added 3 days ago
W
Technical Lead Manager, ML Dataset Platform
Waabi
Toronto, ON
- $200,000 to $280,000 USD / year
- Full-time
Strong software engineering and implementation: You have very strong Python skills and are comfortable in PyTorch training loops; you have strong software-engineering fundamentals and…
Added 3 days ago
AI Engineer – Market Surveillance
Capco
Toronto, ON
Hands-on AI or software engineering experience, with practical skills in Python, SQL and machine learning or LLM-based technologies.
Added 3 days ago
RT
Machine Learning Engineer
Russell Tobin
Toronto, ON
- Contract
Strong Python and machine-learning engineering skills with demonstrated experience taking models from experimentation into reliable production environments. Tech stack: Python, SQL, Power…
Added 3 days ago
A
Business Intelligence Analyst
Apotex
Toronto, ON · North York, ON
- $83,958 to $139,930 CAD / year
…medicines and health products for millions of people worldwide, with a broad portfolio of generic, biosimilar, innovative branded pharmaceuticals and consumer health products. Headquartered…
Added 3 days ago
AI
Business Intelligence Analyst
Apotex Inc.
Toronto, ON · North York, ON
- $83,958 to $139,930 CAD / year
- Full-time
…medicines and health products for millions of people worldwide, with a broad portfolio of generic, biosimilar, innovative branded pharmaceuticals and consumer health products. Headquartered…
Added 3 days ago
TI
Regression Test Engineer with AI/ML
Tekgence Inc
Canada
- Contract
Strong hands-on experience with Python and automated testing.
Added 3 days ago
IG
Artificial Intelligence Engineer
Insight Global
Toronto, ON
- $85 to $94 CAD / hour
- Contract
…complex business problems. Develop and optimize models using Python and PySpark. Work with graph neural networks / graph-based machine learning where appropriate. Build agentic AI solutions…
Added 3 days ago
VS
Machine Learning Engineer
vTech Solution Canada
Toronto, ON
- Contract
Strong Python and machine-learning engineering skills with demonstrated experience taking models from experimentation into reliable production environments. Tech stack: Python, SQL, Power…
Added 3 days ago
TB
Forward Deployed AI Engineer
Type B Digital
Calgary, AB
- Full-time
Strong Python. You should be comfortable with SQL and with building APIs and services (FastAPI or similar).
Added 3 days ago
BC
AI Engineer
BDO Canada
Toronto, ON
- Full-time
Expert‑level proficiency in Python, with working familiarity in Java and/or TypeScript for enterprise application development.
Added 3 days ago
E
RAN System Verification Professional
Ericsson
Ottawa, ON
- Full-time
Work with measurements such as throughput, latency, network load, and user experience
Added 3 days ago
B
Senior Databricks Data Platform Engineer
Brillio
Canada
- Contract
…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…
Added 3 days ago
AC
Data Engineer - Snowflake, dbtCore/Cloud, AWS
Aviva Canada
Markham, ON
- Full-time
3+ years of experience with coding in multiple programming languages such as Python, Java, etc.
Added 3 days ago
VS
Senior Machine Learning Engineer
vTech Solution Canada
Toronto, ON
- Contract
Strong Python and machine-learning engineering skills with demonstrated experience taking models from experimentation into reliable production environments. Tech stack: Python, SQL, Power…
Added 3 days ago
D
Software Engineer Internship - Winter 2027
DataVisor
Remote, Canada
- $40,000 to $50,000 CAD / year
- Full-time
- Remote
…delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's solution scales infinitely…
Added 3 days ago
T
Senior AI Developer / Generative AI Engineer
ThoughtStorm
Toronto, ON
- Contract
Strong hands-on expertise in Python and SQL, with experience in software engineering and developing production-ready AI applications and enterprise solutions.
Added 3 days ago
Data Engineer - Snowflake, dbtCore/Cloud, AWS
Aviva
Markham, ON
3+ years of experience with coding in multiple programming languages such as Python, Java, etc.
Added 3 days ago
E
Applied Researcher
eBay
Toronto, ON
- Full-time
Technical Proficiency: Strong programming skills in Python, Scala, or similar languages. Expertise in machine learning frameworks (e.g. PyTorch/Huggingface/Ray/vLLM) and experience with big…
Added 3 days ago
G
[Disney Dreamlight Valley PC/Console] Analyste de données sénior - Senior Data Analyst
Gameloft
Montreal, QC
- Full-time
Filled with quests, exploration, and engaging activities featuring iconic Disney and Pixar characters, Disney Dreamlight Valley is an original Gameloft Montreal production created by a…
Added 3 days ago
H
Senior WMS Implementation Engineer
Hays
Canada
- $95 to $100 CAD / hour
- Contract
Duration: 12 Months contract with possibility of extension
Added 3 days ago
T
Senior Machine Learning Engineer
TEEMA
Toronto, ON
- Contract
Strong Python and machine-learning engineering skills with demonstrated experience taking models from experimentation into reliable production environments. Tech stack: Python, SQL, Power…
Added 3 days ago
ZS
DevOps Architect
Zodiac Solutions, Inc
Toronto, ON
- Full-time
Hands on scripting skills (python, ruby, perl, etc.)
Added 3 days ago
CT
Senior Applied AI Scientist, Advanced Analytics & Modelling - Customer Intelligence
Canadian Tire Corporation
Toronto, ON
- Full-time
Advanced Python skills and strong experience with SQL, PySpark, and large-scale datasets.

Brillio

Senior Databricks Data Platform Engineer

Canada

Contract

Apply About employer

Applications open in a new tab.

Job details

Job type: Contract
Experience: 7+ years of experience in data engineering, data platform, or DevOps roles, including 3+ years administering and engineering Databricks in an enterprise environment
Posting language: English
Posted: Nov 4, 2026

Original 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 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 CI/CD, 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's 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

CI/CD & Platform Automation

Design, build, and maintain CI/CD 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, 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 showback reporting
Identify and deliver savings through cluster right-sizing, auto-termination, autoscaling tuning, spot and reserved capacity strategies, Photon and serverless evaluation, and workload consolidation
Enforce cost guardrails through cluster policies, budget alerts, and compute governance that prevent waste without slowing teams down
Build dashboards and automated alerts 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, Z-ordering, partitioning strategy, and deletion vectors
Automate table maintenance using predictive optimization, OPTIMIZE, VACUUM, and retention policies to control storage growth and improve query performance
Manage cloud object storage (ADLS Gen2 / S3) layout, lifecycle and tiering policies, and data retention aligned with business and compliance requirements
Tune Spark and SQL workloads by analyzing query profiles, shuffle, skew, caching, and Photon usage to improve speed and reduce cost
Identify and remediate small-file problems, orphaned data, unused tables, and redundant copies across the Lakehouse

Governance, Security & Compliance

Implement secure-by-default platform controls, including private networking, IP access lists, encryption, secrets management, and least-privilege access
Ensure auditable data access and lineage through Unity Catalog, audit logs, and system tables, with appropriate handling of PII and regulatory requirements
Apply data classification, row- and column-level security, and data masking standards across catalogs
Partner with security and compliance teams on platform reviews, vulnerability remediation, and audit evidence

Reliability & Operational Excellence

Define platform SLOs and build monitoring, alerting, and observability for jobs, clusters, warehouses, and pipelines
Lead incident response, root-cause analysis, and post-incident improvements for platform issues, and participate in on-call rotations
Create clear runbooks, standards, and platform documentation that enable self-service and reduce support load
Continuously evaluate new Databricks and cloud capabilities and lead proofs of concept that improve the platform
Mentor engineers, run enablement sessions, and champion platform best practices across McAfee

About you

You are a hands-on platform engineer who thinks in terms of automation, reliability, and unit economics. You enjoy building the systems that make other engineers productive, you are not satisfied until a manual process is codified, and you can explain the cost and performance impact of a platform decision to both engineers and business leaders.

Required Qualifications

7+ years of experience in data engineering, data platform, or DevOps roles, including 3+ years administering and engineering Databricks in an enterprise environment
Deep expertise in Databricks platform administration, including Unity Catalog, workspace and account configuration, cluster policies, SQL warehouses, and Databricks Workflows
Proven experience building CI/CD for data platforms using Databricks Asset Bundles, Terraform, and Azure DevOps, GitHub Actions, or a similar tool
Demonstrated track record of reducing platform cost through compute right-sizing, policy enforcement, and usage analytics, with measurable results
Strong knowledge of Delta Lake internals and storage optimization, including file compaction, clustering, partitioning, and table maintenance
Strong programming skills in Python and SQL, with working knowledge of PySpark and Spark performance tuning
Hands-on experience with at least one major cloud platform (Azure, AWS, or GCP), including networking, identity, and object storage
Experience securing platforms that handle sensitive data, including PII, with attention to compliance and governance

Preferred Qualifications

Experience building agentic or GenAI workflows using Mosaic AI, LangChain, LangGraph, or similar frameworks
Practical knowledge of Model Context Protocol (MCP) to connect enterprise applications and automate platform workflows
Familiarity with Copilot and Anthropic models to enhance development speed, code quality, and documentation
Databricks certifications such as Data Engineer Professional or Platform Administrator
Experience with Databricks system tables, Lakehouse Monitoring, and building FinOps dashboards
Familiarity with Lakeflow / Delta Live Tables, Databricks SQL, Model Serving, and MLOps practices
Knowledge of containerization and orchestration technologies (Docker, Kubernetes)
Experience migrating workloads from legacy platforms (Hadoop, Snowflake, or on-premises warehouses) to Databricks

Personal Attributes

Automation-first mindset, with a habit of eliminating toil and codifying repeatable work
Cost-conscious and data-driven, consistently tying platform decisions to measurable business value
Strong ownership and accountability for platform reliability and the experience of the teams who depend on it
Excellent communication skills, with the ability to influence standards across technical and non-technical stakeholders
Proactive problem-solver with strong analytical and troubleshooting skills
Passionate about emerging technologies, especially in AI, automation, and the Lakehouse ecosystem
Committed to mentoring and knowledge-sharing that elevates the wider engineering team

Why Join Us

This role offers the opportunity to shape the Databricks platform that powers data and AI. You will work with the latest Lakehouse and agentic AI capabilities, see the direct impact of your work on cost, reliability, and developer productivity, and help build the foundation that enables McAfee to protect millions of users worldwide. Join us in creating the next generation of data platforms that will power continued innovation and growth.

Apply About employer

More about this job

Responsibilities

Own and operate the enterprise Databricks Lakehouse platform, including its architecture, governance, security, automation, reliability, and CI/CD. Improve platform cost and performance, develop AI-enabled operational workflows, and partner with teams across engineering, security, finance, and data science to establish standards and enable adoption.

Requirements

Requires 7+ years in data engineering, data platform, or DevOps roles, including 3+ years administering and engineering Databricks in an enterprise environment. Candidates need strong Databricks, Unity Catalog, Terraform, CI/CD, Delta Lake, Python, SQL, cloud, cost optimization, and sensitive-data security experience.

Skills

Unity Catalog
Terraform
CI/CD
Databricks Asset Bundles
Azure DevOps
GitHub Actions
Python
SQL
PySpark
Spark Performance Tuning
Delta Lake Optimization
FinOps
Cloud Networking and Identity
Agentic AI Workflows
Data Governance and Security

Visa sponsorship

Not detected in the job text

Keywords

Databricks
Lakehouse
Unity Catalog
Terraform
Databricks Asset Bundles
Azure DevOps
GitHub Actions
CI/CD
Python
SQL
PySpark
Apache Spark
Delta Lake
FinOps
Mosaic AI Agent Framework
Model Context Protocol
Model Serving
Vector Search
Anthropic Models
Copilot
Lakeflow
Delta Live Tables
Lakehouse Monitoring
Azure
AWS
GCP
ADLS Gen2
S3
SCIM
Docker

Report this job