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Added 39 mins ago
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Senior Technical Analyst / Developer (Machine Learning & Data Engineering)
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Randstad Digital

Senior Technical Analyst / Developer - Machine Learning & Data Engineering

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

$100,000 to $130,000 CAD / year · Full-time

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Job details

Pay: $100,000 to $130,000 CAD / year
Job type: Full-time
Apply by: Dec 6, 2026
Posting language: English
Posted: Nov 6, 2026

Original job description

Senior Technical Analyst / Developer (Machine Learning & Data Engineering)

About Our Client

Our client is one of Canada’s leading and most respected financial services institutions, dedicated to helping Canadian investors build stronger financial futures for over 35 years. Consistently recognized as one of Canada’s Top 100 Employers, they are a privately owned organization known for embracing technological innovation, championing inclusive culture, and providing extensive career growth opportunities across high-performing enterprise teams.

Role Overview

We are seeking a senior, hands-on Senior Technical Analyst / Developer to design, build, deploy, and operationalize enterprise machine learning, data engineering, and AI solutions. In this role, you will bridge the gap between technical analysis, software engineering, and production operations - partnering directly with Data Scientists, Product Owners, Security, and Cloud Architecture teams to scale production data pipelines and generative/agentic AI workflows on AWS, Snowflake, and Informatica Cloud.

Main Responsibilities

Technical Delivery & Architecture: Translate complex business requirements into technical solution designs, architecture blueprints, and implementation roadmaps. Lead technical alignment, perform code reviews, and provide mentorship to engineering peers.
ML, Data & AI Engineering: Build and support production data pipelines, automated integrations, and analytics workflows using Python and SQL. Support data ingestion and processing across AWS, Snowflake, and Informatica Cloud while enforcing data quality, lineage, and source-to-target mapping.
GenAI & Agentic Workflows: Assist in deploying and operationalizing enterprise Generative and Agentic AI applications, including retrieval mechanisms, vector search, tool integrations, and model monitoring.
AWS DevOps & Production Operations: Deploy and monitor ML/data workloads on AWS. Implement CI/CD automation, containerized architectures, CloudWatch logging/alerting, cost governance, and root-cause analysis for production environments.

Must Haves

Education & Experience: Bachelor’s degree in Computer Science, Software Engineering, IT, or equivalent practical experience, paired with 5–8 years of hands-on experience in software development, data engineering, or cloud technical analysis.
Core Tech Stack: Advanced proficiency with Python and SQL for data processing, system integrations, and automation.
MLOps & GenAI: Prior exposure to operationalizing machine learning models (MLOps), RAG architectures, vector search, and agent-based frameworks.
DevOps Tooling: Working knowledge of Docker, container orchestration, workflow schedulers (e.g., Airflow), and Infrastructure as Code (IaC).
Pipelines & Integration: Demonstrated track record building, testing, and supporting enterprise data pipelines and end-to-end data workflows.
Engineering Best Practices: Practical expertise with Git version control, CI/CD pipelines, unit/integration testing, centralized logging, and production troubleshooting.
Cloud Foundation: Direct hands-on experience deploying or supporting workloads within cloud environments (AWS preferred).
Work Authorization: Valid, current Canadian work authorization is required.

Nice to Haves

AWS Ecosystem: Deep hands-on experience with services such as SageMaker, Amazon Bedrock, S3, Lambda, ECS, EKS, or CloudWatch.
Enterprise Data Platforms: Experience working with Snowflake and Informatica Cloud.
Certifications: Cloud or Data certifications (AWS Certified Solutions Architect/Data Engineer, Snowflake, Informatica, etc.).

Other Important Information:

Compensation

Base Salary Range: $100,000 – $130,000 CAD per annum
Incentive Bonus: Target 20% annual performance bonus

Work Model: Hybrid arrangement.

3 Robert Speck Parkway (Mississauga)
2 Days Onsite

Health & Wellness Benefits:

100% employer-paid health, dental, and medical premiums starting on Day 1.
Up to $5,000 annually for mental health services and therapy.
Retirement & Savings: Non-matching corporate group RRSP contribution initiated after 6 months of employment (100% company-funded).

Work-Life Balance & Leave:

Top-up parental leave to 100% of salary for up to 25 weeks.
Generous annual PTO plus 2 paid volunteer days each year.
Additional Perks: Up to $650 home office setup allowance, extensive tuition reimbursement, and access to over 11,000 professional development courses.

📩 How to Apply

If this sounds like a strong fit for your background and you meet the must-have qualifications, please forward your CV directly to me at:

📧 ANDY.WETTLAUFER@RANDSTADDIGITAL.COM

This post is for existing and upcoming vacancies

Apply About employer

More about this job

Responsibilities

Design, build, deploy, and operationalize enterprise machine learning, data engineering, and AI solutions, including production data pipelines and generative or agentic AI workflows. Lead technical design and alignment, support AWS-based production operations and DevOps automation, and collaborate with data science, product, security, and cloud architecture teams.

Requirements

Requires a bachelor’s degree in Computer Science, Software Engineering, IT, or equivalent practical experience, plus 5–8 years of relevant hands-on experience. Candidates need advanced Python and SQL skills, experience with enterprise data pipelines and cloud workloads, exposure to MLOps and GenAI approaches, familiarity with DevOps tools and engineering practices, and current Canadian work authorization.

Skills

Python
SQL
Machine Learning
Data Engineering
Generative AI
MLOps
RAG Architectures
Vector Search
AWS
Snowflake
Informatica Cloud
Docker
Airflow
Infrastructure as Code
CI/CD
Data Pipelines

Benefits

Employer-Paid Health, Dental, and Medical Insurance
Mental Health Services Coverage
Parental Leave Salary Top-Up
Paid Time Off
Paid Volunteer Days
Home Office Setup Allowance
Tuition Reimbursement
Professional Development Courses

Visa sponsorship

Not detected in the job text

Hiring contact email

ANDY.WETTLAUFER@RANDSTADDIGITAL.COM

Keywords

Python
SQL
AWS
Snowflake
Informatica Cloud
Machine Learning
MLOps
Generative AI
Agentic AI
RAG
Vector Search
Data Engineering
Data Pipelines
Data Quality
Data Lineage
Docker
Container Orchestration
Airflow
Infrastructure as Code
Git
CI/CD
Unit Testing
Integration Testing
CloudWatch
SageMaker
Amazon Bedrock
S3
Lambda
ECS
EKS

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