Customer Engineer, Analytics and ML Products
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Before you apply
LocationToronto, Canada - Remote
Work moderemote
Typefull-time
SeniorityMid
Experience5+ yrs
DepartmentCustomer Implementation
Company size4+ people
PostedMay 22, 2025 · 1y ago
Verified live2d ago
May no longer be actively hiring
Posted by the company on May 22, 2025
At a glanceSummarised by Seekless from the posting.
Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
At least 2 years of full-stack development experience
5+ years in analytics, data science, or ML-focused roles
Proficiency in SQL and Python
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
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
Containerization (Docker/Kubernetes)
Experience with digital marketing analytics
Comfort in startup environments
Skills
SQL
Python
BigQuery
Vertex AI
Looker
Looker Studio
Ruby
Docker
Kubernetes
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:
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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.
Hiring process
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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.
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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.
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