Why This Job is Featured on The SaaS Jobs
This Analytics Engineer role sits at the intersection of SaaS product analytics and the emerging operational layer for agentic AI, where voice and chat experiences behave more like continuously tuned services than static features. The emphasis on ASR and NLP evaluation, plus instrumentation for logging and monitoring, reflects a SaaS environment where conversational systems must be observed in production-like conditions and improved through measurable feedback loops.
For a SaaS career, the long-term value comes from building the habits and tooling that make analytics actionable across teams. Experience designing reliable event capture, shaping datasets for decision-making, and connecting dashboards to real product changes translates well to data platforms, product analytics, and ML-adjacent roles inside subscription businesses. Work on automated QA and workflow automation also develops an engineering mindset around repeatability and operational efficiency, which becomes increasingly important as AI capabilities move from prototypes to maintained product surfaces.
This position suits an early-career data or software practitioner who prefers collaborative problem-solving over isolated reporting work. It will fit someone who enjoys moving between analysis, pipeline development, and quality validation, and who is motivated by improving system performance through evidence rather than intuition. Comfort working with multiple stakeholders across AI, engineering, and product will be a strong indicator of fit.
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.
