Jobs in Canada

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Added 6 days ago
PC
AML Analytics Manager
Pwc Canada
Toronto, ON
- Full-time
Lead end-to-end delivery of AML Analytics projects, including project planning, team management, client engagement, project economics, and quality of deliverables.
Added 6 days ago
Senior Data Engineer - Vancouver
Capgemini
Vancouver, BC
…help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive…
Added 6 days ago
Senior Data Engineer
Capgemini
Vancouver, BC
…help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive…
Added 6 days ago
Senior Technology Specialist, Integration
Equitable
Waterloo, ON
The Senior Technology Specialist, Integration will be accountable for the solutioning of the API Management components, will manage APIM service instances and create the APIs, operations,…
Added 6 days ago
NS
Azure Databricks Solutions Architect
N2P Systems
Toronto, ON
- Full-time
We are seeking an experienced Azure Databricks Solutions Architect to lead enterprise-scale data architecture, engineering, analytics, and cloud modernization initiatives.
Added 6 days ago
E
Senior Technology Specialist, Integration
Equitable
Waterloo, ON
- $85,000 to $110,000 CAD / year
- Full-time
The Senior Technology Specialist, Integration will be accountable for the solutioning of the API Management components, will manage APIM service instances and create the APIs, operations,…
Added 6 days ago
AI
Practice Lead - Data & AI
Architecture in Motion Inc.
Mississauga, ON
- Full-time
AIM is seeking a Data & AI Practice Lead to build and lead our Microsoft-focused Data & AI practice.
Added 6 days ago
XS
Senior Databricks Architect
Xaxis Solutions
ON · Ontario, Canada
- Contract
Must have hands-on experience delivering at least one end-to-end Databricks implementation · Please prioritize candidates who have strong hands-on Databricks + AWS experience and are comfortable working onsite 3 days per week from Day 1
Added 6 days ago
NS
Azure Databricks Solutions Architect
N2P Systems
Toronto, ON
- Full-time
We are seeking an experienced Azure Databricks Solutions Architect to lead enterprise-scale data architecture, engineering, analytics, and cloud modernization initiatives.
Added 7 days ago
GT
Lead Data Engineer / Data Product Lead – Snowflake
Global Technical Talent, an Inc. 5000 Company
Toronto, ON
- $60 to $80 CAD / hour
- Contract
This client is seeking an experienced Sr. Data Engineer / Data Product Lead to support the design and delivery of enterprise-scale data products within a complex life sciences environment.…
Added 7 days ago
B
Senior Databricks Data Platform Engineer
Brillio
Canada
- Contract
…and you will measure your success in platform reliability, developer productivity, and dollars…
Added 7 days ago
R
Data Scientist
Raise
Calgary, AB
- Full-time
Design, build, test, and optimize scalable data models and ETL/ELT pipelines within Databricks using Python, PySpark, SQL, notebooks, workflows, and orchestration frameworks to support…
Added 7 days ago
A
Power BI & Azure Platform Engineer / Toronto, ON (Onsite) - FTE
AceStack
Toronto, ON
- Full-time
Develop data transformation solutions using SQL, Python, and PySpark.
Added 7 days ago
CT
Senior ML/AI Engineer, Advanced Analytics & Modelling - Customer Intelligence Platforms
Canadian Tire Corporation
Toronto, ON
- Full-time
Location: Toronto, Ontario (Hybrid: In-office 4 days per week)
Added 7 days ago
M
Senior Data Architect
Miratech
Mississauga, ON
- Full-time
Working Model: This is a hybrid role requiring 2 days per week in a downtown Toronto office
Added 7 days ago
A
Data Analytics Lead
Altis
Markham, ON
- $110,000 to $125,000 CAD / year
- Full-time
…a Senior Data Engineer / Senior BI / Analytics Engineering Lead to design, build, and optimize scalable data solutions that support business intelligence, reporting, and advanced analytics.…
Added 7 days ago
W
Data Engineer
Wiraa
Canada
- Full-time
We are seeking a full-time Data Engineer to join our IT team in Langley, BC. Reporting to the Team Lead, Data & Analytics, this role offers the opportunity to work with one of the largest…
Added 8 days ago
KG
Enterprise Data Architect – Snowflake & Cortex
K&K Global Talent Solutions INC.
ON · Ontario, Canada
- Full-time
…AI enablement, you will design scalable Lakehouse solutions, lead platform migrations, and establish governance, security, and responsible AI standards. This role requires deep expertise in…
Added 9 days ago
C
Expert AI Engineering-CA
CN
Quebec, QC
- Full-time
Between 2 to 5 years of experience in software engineering, data engineering, machine learning engineering, AI engineering, or related technology delivery roles
Added 9 days ago
Data Analyst Developer – ETL/ELT & Data Pipelines
Vacances Air Canada Vacations / Air Canada Rouge
Mississauga, ON · Montreal, QC
Hybrid work model: Corporate Mandate of 4 days in office (Tuesday, Wednesday, Thursday + 4th day of your choice) and 1 day from home
Added 9 days ago
IF
Senior Data Analyst - Operational Performance Analytics
Intact FC
Montreal, QC
- Full-time
…Underwriting Operations. We are looking for a Senior Data Analyst to lead Power BI solution design and play a key role in the SAS-to-Databricks migration (PySpark/SQL). This position offers…
Added 12 days ago
PF
Data Engineer
Pattison Food Group
Langley (District), BC · Langley Office - Langley BC
- Full-time
Reporting to the Team Lead, Data & Analytics, you will be responsible for working with one of the largest, most comprehensive datasets in Canada while delivering and pioneering solutions…
Added 12 days ago
UC
Databricks Data Platform Engineer
Univedge Consulting LLC
Canada
- Contract
…and you will measure your success in platform reliability, developer productivity, and dollars…
Added 12 days ago
Senior Data Engineer
Capgemini
Calgary, AB
Description and Location Strong/expert Spark (PySpark) Using Jupyter Notebooks, Colab or DataBricks (preferred) Hands-on data pipeline development, ingest patterns in Azure Orchestration…
Added 12 days ago
NS
AWS Snowflake Solutions Architect
N2P Systems
Toronto, ON
- Full-time
N2P Systems is seeking an experienced AWS Snowflake Solutions Architect to join our enterprise technology delivery team in Toronto, Ontario, Canada. At N2P Systems, you will put 10+ years…

Brillio

Senior Databricks Data Platform Engineer

Canada

Contract

Apply on LinkedIn About employer

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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 on LinkedIn 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

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Work requirements

Jobs in Canada