Senior Analytics Engineer - CANADA (Remote)

Act as data liaison between Engineering, GTM, and Finance — ensuring consistent metric definitions and proper system instrumentation.

Enable stakeholder self-service access to trusted insights.

Drive data literacy: evangelize best practices in querying, dashboarding, and interpreting metrics; coach stakeholders toward self-serve.

Design and maintain Snowflake Cortex semantic views that serve as the governed data interface for AI agents and LLM-powered tools.

Partner with AI/product teams to scope, build, and validate the semantic layer definitions that power internal AI assistants.

Build measurement frameworks for AI-powered initiatives — including experiment design and attribution modeling.

Experience building and maintaining Airflow DAGs and orchestrating multi-source API ingestion pipelines.

Strong foundation in statistics and experiment design — A/B testing, significance testing, and measuring incremental impact.

Experience with predictive modeling fundamentals — classification, feature selection, and model evaluation.

Familiarity with financial SaaS metrics and billing operations (ARR/MRR/NRR, subscription reconciliation, revenue recognition).

Experience with people analytics (headcount, attrition, compensation benchmarking).

Establish a trusted, well-modeled analytics layer that product managers, marketers, and leaders rely on daily.

Improve data quality and reliability, with clear SLAs and observability around our most critical models.

Drive down time-to-insight by enabling self-serve access to high-quality datasets and metrics.

Extreme ownership over critical infrastructure and data models that directly impact product decisions and business growth.

Partner with data engineers and analysts to build a semantic layer that AI agents can use to answer stakeholder questions — and actively maintain the semantic views that power those agents.

Proactively identify and quantify data discrepancies across systems and drive them to resolution with operational teams.

Design measurement frameworks for new initiatives — defining what to track, how to measure impact, and what "success" means before launch.