Customer Engineer, Analytics and ML Products
Toronto
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingYou’ll ensure that features are deployed and delivered to clients with the highest quality and measurable impact.
Work across the full tech stack—both for building user-facing features and analytical tools.
You'll design scalable data pipelines, integrate ML models into production systems, and support experimentation frameworks (e.g., incrementality testing).
From the employer’s posting
We're looking for a Customer Engineer who’s deeply passionate about analytics and machine learning (ML). In this role, you’ll be the bridge between technical challenges and client needs—translating real-world data problems into scalable analytics solutions and intelligent ML features. Your work will directly impact the way clients experience and derive value from Switch’s data and ML products. This is a technical role that leans heavily on data engineering, data science, analytics, and ML infrastructure, while still involving front-end and back-end development and product management. You’ll ensure that features are deployed and delivered to clients with the highest quality and measurable impact. This position touches every part of the Switch ecosystem, making it ideal for someone who thrives in interdisciplinary environments and who’s motivated by improving both internal systems and client outcomes through data-driven solutions. Key Responsibilities
Full-Stack + Data & ML Development: Work across the full tech stack—both for building user-facing features and analytical tools. Your stack may include SQL, BigQuery, Python (for analytics/ML), and Ruby or modern front-end frameworks. You'll design scalable data pipelines, integrate ML models into production systems, and support experimentation frameworks (e.g., incrementality testing). Collaborative Innovation with a Data Focus:
What you’ll bring
All qualificationsCore experience
- Proficiency in SQL and Python, and familiarity with data platforms like BigQuery, Vertex AI, or similar tools.
- Demonstrated experience designing and maintaining scalable, reliable data pipelines and ML models.
- Familiarity with tools like Looker/Looker Studio for reporting, and experience with marketing experiments, ROI modelling, or statistical analysis.
- Strong communication skills with a knack for storytelling through data to both technical and non-technical audiences.
- Experience with agile methodologies, DevOps, and optionally MLOps/DataOps workflows.
Qualification wording
Proficiency in SQL and Python, and familiarity with data platforms like BigQuery, Vertex AI, or similar tools.
Demonstrated experience designing and maintaining scalable, reliable data pipelines and ML models.
Familiarity with tools like Looker/Looker Studio for reporting, and experience with marketing experiments, ROI modelling, or statistical analysis.
Strong communication skills with a knack for storytelling through data to both technical and non-technical audiences.
Experience with agile methodologies, DevOps, and optionally MLOps/DataOps workflows.
Education & alternatives
Qualifications A Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field. - At least 2 years of full-stack development experience and 5+ years in analytics, data science, or ML-focused roles.
Tools in this posting
- Python
- Ruby
- SQL
- BigQuery
- Looker
- Docker
- Kubernetes
Source — Tool mentions in context
Full-Stack + Data & ML Development: Work across the full tech stack—both for building user-facing features and analytical tools. Your stack may include SQL, BigQuery, Python (for analytics/ML), and Ruby or modern front-end frameworks. You'll design scalable data pipelines, integrate ML models into production systems, and support experimentation frameworks (e.g., incrementality testing). Collaborative Innovation with a Data Focus:
- At least 2 years of full-stack development experience and 5+ years in analytics, data science, or ML-focused roles. - Proficiency in SQL and Python, and familiarity with data platforms like BigQuery, Vertex AI, or similar tools. - Demonstrated experience designing and maintaining scalable, reliable data pipelines and ML models.
- Demonstrated experience designing and maintaining scalable, reliable data pipelines and ML models. - Familiarity with tools like Looker/Looker Studio for reporting, and experience with marketing experiments, ROI modelling, or statistical analysis. - Strong communication skills with a knack for storytelling through data to both technical and non-technical audiences.
- Experience with agile methodologies, DevOps, and optionally MLOps/DataOps workflows. - Bonus: Containerization (Docker/Kubernetes), experience with digital marketing analytics, and comfort in startup environments. Your Expected Progression at Switch:
Job description
Customer Engineer - Analytics and ML
We're looking for a Customer Engineer who’s deeply passionate about analytics and machine learning (ML). In this role, you’ll be the bridge between technical challenges and client needs—translating real-world data problems into scalable analytics solutions and intelligent ML features. Your work will directly impact the way clients experience and derive value from Switch’s data and ML products.
This is a technical role that leans heavily on data engineering, data science, analytics, and ML infrastructure, while still involving front-end and back-end development and product management. You’ll ensure that features are deployed and delivered to clients with the highest quality and measurable impact. This position touches every part of the Switch ecosystem, making it ideal for someone who thrives in interdisciplinary environments and who’s motivated by improving both internal systems and client outcomes through data-driven solutions.
Key Responsibilities
Client-Focused Analytics Solutions:
Act as the technical liaison for our clients, understanding their data and analytics challenges and transforming feedback into predictive models, dashboards, or automated ML features. You’ll diagnose issues in data pipelines, analytics tooling, and ML workflows, while clearly explaining technical concepts to a variety of stakeholders.
Full-Stack + Data & ML Development:
Work across the full tech stack—both for building user-facing features and analytical tools. Your stack may include SQL, BigQuery, Python (for analytics/ML), and Ruby or modern front-end frameworks. You'll design scalable data pipelines, integrate ML models into production systems, and support experimentation frameworks (e.g., incrementality testing).
Collaborative Innovation with a Data Focus:
Partner closely with our business team to uncover insights from client data, identify common analytical needs, and proactively develop tools like custom dashboards, measurement models, and centralized ML infrastructure. You'll play a key role in shaping our analytics and ML product roadmap.
Qualifications
A Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
- At least 2 years of full-stack development experience and 5+ years in analytics, data science, or ML-focused roles.
- Proficiency in SQL and Python, and familiarity with data platforms like BigQuery, Vertex AI, or similar tools.
- Demonstrated experience designing and maintaining scalable, reliable data pipelines and ML models.
- Familiarity with tools like Looker/Looker Studio for reporting, and experience with marketing experiments, ROI modelling, or statistical analysis.
- Strong communication skills with a knack for storytelling through data to both technical and non-technical audiences.
- Experience with agile methodologies, DevOps, and optionally MLOps/DataOps workflows.
- Bonus: Containerization (Docker/Kubernetes), experience with digital marketing analytics, and comfort in startup environments.
Your Expected Progression at Switch:
- Month 1: You’ve met our clients and understand their core data challenges. You've begun monitoring daily data fidelity, assisted with client dashboards and resolved basic pipeline issues. You can independently fix data bugs and write simple predictive models.
- Month 3: You’ve built or optimized pipelines for multiple client-facing metrics, implemented your first client-facing ML feature or experiment, and are helping automate common requests. Your analytical insights are directly influencing onboarding and product success.
- Month 6: You’re independently owning ML and analytics initiatives—from experimentation to deployment. You’re creating internal documentation and tooling that allow teams to self-serve analytics. You’re a trusted advisor on data strategy and contribute regularly to the product roadmap through insight and initiative.
If you're someone who thrives at the intersection of data, engineering, and customer impact, and you're excited to create intelligent data systems and client-facing ML features, we’d love to talk to you. Join us in helping our clients solve complex marketing and analytics problems, while building a team rooted in technical excellence and data-driven decision-making.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
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Source & posting history
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Toronto
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- Status in our records
- Active
- First seen by us
- Jun 2, 2026
- Recorded sightings
- 42
- Last seen by us
- Sep 29, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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