Customer Engineer - Analytics and ML

Key Responsibilities

Qualifications

• 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.