Why This Job is Featured on The SaaS Jobs
Analytics engineering roles are increasingly central in SaaS as products add AI-driven features that must be measured, debugged, and improved in production. This position stands out for its focus on agentic voice and chat systems, where instrumentation, evaluation, and monitoring become part of the product itself. The Vancouver office setting also signals a role embedded closely with engineering and AI stakeholders rather than operating as a distant reporting function.
For a SaaS career, the combination of data pipelines, analytics, and QA is durable leverage. Work like logging strategy, automated evaluation, and dashboarding maps directly to how subscription products manage reliability and customer outcomes over time. Experience supporting ASR and NLP initiatives also builds fluency in modern SaaS data problems, including feedback loops, model performance drift, and the operational discipline required to keep AI features trustworthy.
This role fits someone who enjoys cross-functional work and prefers translating ambiguous product behavior into measurable signals. It will suit an early-career to mid-level practitioner who wants hands-on ownership across SQL, Python, and cloud tooling while staying close to product decision-making. An interest in conversational AI and a bias toward automation and process improvement will align well with the day-to-day focus.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Your role
As an analytics engineer, you’ll be an integral part of our data analysis and QA team, providing essential data support for our cutting-edge Agentic AI initiatives, specifically with ASR and NLP teams. A key focus will be on leveraging data analysis to identify and drive optimization of the conversational flows and underlying data infrastructure for agentic voice and chat solutions. You will actively seek opportunities to improve the team’s productivity and workflow through automation and process optimization, including implementing automated QA for our agentic systems.
This position reports to the manager of the Data Analysis and QA team and has the opportunity to be based in our Vancouver, Canada Office.
What you’ll do
- You will work closely with other Agentic AI teams to test and evaluate our Agentic voice and chat solutions.
- You will design and implement data logging and monitoring strategies to capture key analytical insights.
- You will utilize data analysis to identify areas for optimization in the voice bot's conversational flows and data pipeline.
- You will build and maintain data pipelines on Vertex AI pipelines.
- You will work closely with the AI Platform team to build tooling for data science projects.
- You will implement automation and processes to improve our workflow.
- You will create and maintain dashboards (Tableau) and data pipelines (Dataform) that help drive product and business decisions.
- You will contribute to our continuous efforts to enforce data privacy and compliance.
- You will collaborate with cross-functional teams, including AI, engineering, and product teams.
Skills you’ll bring
- Bachelor's or Master’s degree in Computer Science, Software Engineering, or related fields.
- 1 - 3 years of working experience with software engineering or data engineering projects.
- 1 - 3 years of experience with Python, working with GCP, including storage, BigQuery, Compute, Kubernetes, or similar.
- 1 - 3 years of experience with SQL, able to optimize complex SQL queries and build data pipelines.
- Experience with BI tools such as Tableau.
- Experience analyzing the performance of conversational AI systems (e.g., voice bots, chatbots) and collaborating with cross-functional teams (AI, Product) on data-driven improvements.
- Experience working with popular LLM frameworks.
- Strong problem-solving and analytical abilities, with the capacity to handle complex technical and analytical problems.
