Senior Machine Learning Engineer

Capgemini; Mississauga; On-site; CAD 146,000 - 173,000; Full time

Benefits offered by this job

Paid time off

Medical/dental coverage

Retirement savings plans

Life and disability insurance

Employee assistance programs

Other benefits

Job summary

Capgemini in Canada seeks a machine learning professional to design and optimize data pipelines, manage ETL processes and contribute to scalable analytics infra.

You will collaborate with executives, product, data, and design teams, lead 10-15 team members, and help deploy and monitor ML models. The role requires strong Azure, Spark, SQL and Python skills, plus clear communication and presentation abilities, with a comprehensive benefits package.

Qualifications

• Knowledge of data pipeline architecture and ETL design using Azure tools.
• Experience building and maintaining large-scale data sets and pipelines.
• Strong communication with stakeholders across Exec, Product, and Design teams.
• Ability to lead and mentor a 10–15 person team.

Responsibilities

• Create and maintain optimal data pipeline architecture using ADF.
• Able to create ETL through Azure Data Bricks and good understanding of Spark framework.
• Assemble large, complex data sets that meet functional/non-functional business requirements.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure big data technologies.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.
• Ability to lead 10-15 team members.
• Good presentation and communication skills.

Skills

Communication skills

Presentation skills

Tools

Azure Data Factory

Azure Databricks

Azure Machine Learning

PySpark

SQL

Python

Power BI

AWS

Salesforce

DevOps

Azure Security

Job description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired bya collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizationsunlock the value of technology and build a more sustainable, more inclusive world.

Required Skills

Azure data factory, Azure data bricks, Azure Machine Learning, PySpark, SQL, Python, PB, AWS, SF, DEVOPS and Azure Security

Job Description

• Create and maintain optimal data pipeline architecture using ADF.
• Able to create ETL through Azure data bricks and good understating of spark framework.
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure 'big data' technologies.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.
• Ability to lead 10-15 team members.
• Good presentation and communication skills.

The role of a machine learning professional involves applying machine learning techniques and algorithms to solve complex problems, analyze data, and develop intelligent systems.

Job Description - Grade Specific

Plays a critical role in leading and supporting machine learning initiatives. Combined with technical expertise and management skills to drive successful project execution, deploying and mointoring the models, foster collaboration, and align machine learning strategies with broader business goals.

The base compensation range for this role in the posted location is $105,392 to $125,088.

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Capgemini Offers a Comprehensive, Non-negotiable Benefits Package To All Regular, Full-time Employees.

In The U.S. And Canada, Available Benefits Are Determined By Local Policy And Eligibility And May Include:

• Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Other benefits as provided by local policy and eligibility

Important Notice:

Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.

Disclaimers

Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.

This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.