Product Analyst, Data Platform and Analytics

Caseware•Toronto, ON

1d•Hybrid

About The Position

Caseware is a leading company in the audit and accounting software industry with a global presence. The company is seeking a Product Analyst, Data Platform and Analytics to join their Product Organization and contribute to a metric-driven culture. This role will collaborate with Product, Design, Finance, Commercial, and Engineering Teams to define success metrics, develop analytical frameworks, design experiments, and ensure data-driven decision-making in product development. This is a full-time, permanent, and new position located in Toronto, requiring 3 days a week in the office.

Requirements

3+ years in product, business, or data analytics in a SaaS or technology environment.
Solid grounding in SQL and Python for writing queries, wrangling data, and working with APIs.
Hands-on experience with data lakehouse platforms (Microsoft Fabric, Databricks, Snowflake, or similar); ability to work with engineering teams to improve pipeline quality and schema design.
Experience with BI and visualization tools; Power BI and Microsoft Fabric are a strong plus.
Familiarity with product analytics platforms (Pendo, Amplitude, Mixpanel, or similar) and AI observability tools such as Langfuse.
Proven ability to build funnel analyses, cohort studies, and retention models, and explain their implications and recommended actions.
Comfortable operating in messy data environments, assessing data quality, making defensible assumptions, and communicating confidence levels.
Habitual AI user, utilizing AI tools to accelerate analysis, pressure-test logic, generate hypotheses, and move faster.
Curious about how AI systems behave and interested in measuring them (trace analysis, quality evaluations, model observability).
Strong data storytelling skills to translate complex analysis into clear narratives for non-technical audiences.
Self-starter with high agency, comfortable driving workstreams independently in fast-moving, ambiguous environments.

Responsibilities

Own end-to-end product analytics across the full data stack, from pipeline work in the data lakehouse (Microsoft Fabric / Delta Lake) to insight delivery, ensuring data is clean, trusted, and decision-ready.
Conduct deep AI trace analysis using Langfuse and similar observability tooling to surface patterns in model behavior, latency, quality, and user interaction across AI-powered features.
Build and own funnel analysis across the customer lifecycle (activation, adoption, engagement, retention), identifying drop-off points and quantifying the impact of product changes.
Define, track, and report on core product and revenue metrics including NPS, ARR per user, active users, feature adoption rates, and firm-level engagement signals.
Build dashboards and scalable reporting in Power BI (Microsoft Fabric) that unify data across systems and make insights accessible to the full organization.
Synthesize data into clear, opinionated recommendations that influence product prioritization and roadmap decisions.
Partner with Product Managers to validate hypotheses, run experiments, and measure feature performance with statistical rigor.
Tackle data quality issues by diagnosing gaps, inconsistencies, and structural issues across the data estate, and work with engineering to resolve them.
Work with incomplete, inconsistent, and loosely structured data to produce reliable, high-trust outputs.