Senior Analytics Engineer – CANADA

About This Opportunity

We are representing a well-funded Series C technology company in the real estate sector that has achieved significant scale and growth. Our client is seeking a Senior Analytics Engineer based in Canada to build and scale the analytical foundation that powers decision-making across their organization.

This role sits at the intersection of data engineering and analytics, transforming raw product, marketing, financial, and operational data into clean, well-modeled, and trustworthy datasets. You'll power everything from executive dashboards and cohort analyses to experimentation, billing operations, and semantic layers that enable AI agents to answer stakeholder questions autonomously.

Responsibilities

Build & Own the Data Foundation

• Own and evolve the dbt project, ensuring models are performant, well-tested, and documented
• Design and maintain the Snowflake data warehouse and ingestion processes
• Use modern data modeling best practices to create core entities and datasets that account for complex business processes and logic
• Build and maintain custom Python/Airflow pipelines to ingest data from third-party APIs into Snowflake
• Design and operate cross-system reconciliation models that compare data across source systems to surface discrepancies and protect revenue

Drive Data Quality & Automation

• Implement testing and observability for analytics pipelines
• Enforce CI/CD best practices, including automation, linting, tests, code review, and approvals
• Standardize metric definitions and ensure they are consistently computed across tools
• Investigate and document data incidents end-to-end, from root cause analysis through remediation tracking and stakeholder communication

Cross-Functional Collaboration

• Act as data liaison between Engineering, GTM, and Finance teams, ensuring consistent metric definitions and proper system instrumentation
• Enable stakeholder self-service access to trusted insights
• Drive data literacy by evangelizing best practices in querying, dashboarding, and interpreting metrics
• Coach stakeholders toward self-serve analytics capabilities

Build AI-Ready Data Infrastructure

• Design and maintain Snowflake Cortex semantic views that serve as the governed data interface for AI agents and LLM-powered tools
• Partner with AI and product teams to scope, build, and validate semantic layer definitions
• Build measurement frameworks for AI-powered initiatives, including experiment design and attribution modeling

What We're Looking For

Required Qualifications:

• 5+ years of experience as an analytics engineer, data engineer, or similar role in a SaaS environment
• Deep expertise in SQL, dbt, and modern data modeling best practices
• Proficiency in Python for pipeline development, API integrations, and automation
• Experience modeling Salesforce data, including opportunities, contracts, subscriptions, cases, and field history
• Proven experience building custom ELT pipelines that ingest data from third-party APIs into a cloud data warehouse
• Experience designing cross-system reconciliation models to surface data discrepancies
• Proven experience working with event-based and product usage data (e.g., Posthog, Mixpanel)
• Experience connecting marketing data (paid ads, campaigns, attribution) to product analytics
• Experience designing and maintaining semantic layers that serve as governed data interfaces (dbt Semantic Layer, Snowflake Cortex, or similar)
• Comfortable with large-scale data systems (Snowflake, BigQuery, Redshift)
• Strong familiarity with CI/CD, Git-based workflows, and automated testing
• Experience collaborating cross-functionally with engineers, analysts, and product managers
• Demonstrated success using analytics to drive decisions in a technical or product-focused environment
• Comfort taking ownership of ambiguous problems and designing end-to-end solutions

Preferred Qualifications:

• Experience building and maintaining Airflow DAGs and orchestrating multi-source API ingestion pipelines
• Strong foundation in statistics and experiment design, including A/B testing and significance testing
• Experience with predictive modeling fundamentals (classification, feature selection, 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)

How We Work with You

When you apply through Get A Job.ai, our recruiting team will review your background and schedule an initial conversation to understand your experience and career goals. If there's a strong mutual fit, we will submit your profile to our client for consideration. Throughout the interview process, we'll provide guidance and feedback to help you succeed.

Please note that all applications must come through Get A Job.ai. We ask that you do not contact the client directly, as this allows us to best represent your candidacy and coordinate the hiring process effectively.

Pay

Compensation details will be discussed during the screening process and are competitive with senior analytics engineering roles in the Canadian market.

Equal Opportunity

Get A Job.ai is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.