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Sr. Technical Analyst - Hybrid

  • Mississauga, ON, Canada

$110,000 to $130,000 CAD / year · Full-time

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Job details

Pay
$110,000 to $130,000 CAD / year
Job type
Full-time
Apply by
Experience
5-8 years of experience in software development, data engineering, cloud engineering, technical analysis or a related role.
Posting language
English
Posted

Original job description

We are seeking a Senior Technical Analyst / Developer to design, develop, deploy and support machine learning, data and AI solutions. This senior hands-on role combines technical analysis, software development, data engineering, cloud deployment and production support.

The successful candidate will work closely with Product Owners, Data Scientists, business teams, Architecture, Security, Cloud and Data teams to deliver reliable, secure and supportable solutions across AWS, Snowflake and Informatica Cloud. The role also provides technical guidance, code reviews and mentoring to team members.


Advantages
Experience with AWS SageMaker, Amazon Bedrock, S3, Lambda, ECS, EKS or CloudWatch.
Experience with Snowflake and Informatica Cloud.
Experience with Docker, infrastructure as code and workflow orchestration.
Experience operationalizing machine learning models and implementing MLOps practices.
Experience with Generative AI, retrieval-augmented generation, vector search or agent-based solutions.
Experience with REST APIs, enterprise integrations and cloud-security practices.
Experience with data quality, lineage, metadata and source-to-target mapping.
AWS, Snowflake, Informatica, DevOps or data-engineering certifications are considered assets.

Responsibilities
Technical Delivery

Translate business and technical requirements into practical solution designs and implementation plans.
Provide day-to-day technical guidance and support delivery planning, prioritization and dependency management.
Review technical solutions for alignment with engineering, architecture, security and data standards.
Communicate delivery progress, risks, dependencies and production issues to stakeholders.
Support code reviews, knowledge sharing, mentoring and continuous improvement.

Machine Learning, Data and AI Engineering

Develop, deploy and support production machine learning models, analytical solutions and data pipelines.
Build Python and SQL-based automation, integrations and data-processing components.
Support data ingestion, transformation and processing across AWS, Snowflake and Informatica Cloud.
Implement model versioning, testing, deployment, monitoring and documentation practices.
Promote data quality, lineage, source-to-target mapping and clear production ownership.
Support approved Generative and Agentic AI solutions, including retrieval workflows, enterprise data connections, tool integrations and monitoring.

AWS DevOps and Production Operations

Deploy and operate machine learning, data and AI workloads on AWS.
Develop and maintain CI/CD pipelines, containerized solutions and infrastructure automation.
Work with AWS services such as SageMaker, Bedrock, S3, Lambda, ECS, EKS and CloudWatch.
Implement logging, monitoring, alerting, cost controls and operational runbooks.
Coordinate production releases, deployment validation, incident investigation and operational handover.
Troubleshoot application, data, infrastructure and model-processing issues and perform root-cause analysis.
Collaborate with Architecture, Security, Cloud and Data teams to deliver reliable production solutions.

Qualifications
Degree in Computer Science, Software Engineering, Information Technology or a related field, or equivalent experience.
5-8 years of experience in software development, data engineering, cloud engineering, technical analysis or a related role.
Strong hands-on experience with Python and SQL.
Experience developing and supporting data pipelines, automation and system integrations.
Experience with Git, CI/CD, automated testing, logging and production support.

Summary
The Skill Set You Bring

Strong analytical, troubleshooting and problem-solving skills.
Ability to translate requirements into technical specifications and working solutions.
Strong communication and stakeholder-management skills.
Ability to work independently while contributing to team delivery and technical standards.
Experience deploying or supporting workloads on AWS.

Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.

Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.

This posting is for existing and upcoming vacancies.
More about this job

Responsibilities

The Senior Technical Analyst at Randstad Canada will translate requirements into working data and AI solutions, build and deploy machine learning pipelines, and run them in production on AWS. The role also guides the team through code reviews, release coordination and incident follow-up.

Requirements

Candidates need 5-8 years in software development, data engineering, cloud or technical analysis, with strong hands-on Python and SQL. Experience with AWS, data pipelines, CI/CD and production support is required.

Skills

  • Python
  • SQL
  • AWS
  • Amazon SageMaker
  • Amazon Bedrock
  • Amazon S3
  • AWS Lambda
  • Amazon ECS
  • Amazon EKS
  • Amazon CloudWatch
  • Snowflake
  • Informatica Cloud
  • Docker
  • Infrastructure as code
  • Workflow orchestration
  • MLOps
  • Machine learning model deployment
  • Generative AI
  • Retrieval-augmented generation
  • Vector search
  • REST APIs
  • Git
  • CI/CD
  • Automated testing
  • Data pipelines

Categories

  • Technology
  • Data & Analytics
  • Software

Keywords

  • Senior Technical Analyst
  • Machine Learning Engineer
  • Data Engineer
  • AI Developer
  • Python
  • SQL
  • AWS
  • SageMaker
  • Amazon Bedrock
  • Snowflake
  • Informatica Cloud
  • MLOps
  • Docker
  • CI/CD
  • Generative AI
  • Retrieval-augmented generation
  • Hybrid

Seniority

Senior

Tools

  • AWS SageMaker
  • Amazon Bedrock
  • Amazon S3
  • AWS Lambda
  • Amazon ECS
  • Amazon EKS
  • Amazon CloudWatch
  • Snowflake
  • Informatica Cloud
  • Docker

Languages

  • English

Fields of study

  • Computer Science
  • Software Engineering
  • Information Technology

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