Senior Analytics Engineer
New
L
Luxury PresenceReal Estate Tech
CANADA (Remote)Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLGitSalesforceSnowflakeAirflowCI/CDData modelingdbt
Requirements
- 5+ years of experience as an analytics engineer, data engineer, or a 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, and cases.
- Proven experience building custom ELT pipelines that ingest data from third-party APIs into a cloud data warehouse.
- Experience designing cross-system reconciliation models.
- Proven experience working with event-based and product usage data such as Posthog or Mixpanel.
- Experience connecting marketing data to product analytics.
- Experience designing and maintaining semantic layers like dbt Semantic Layer or Snowflake Cortex.
- Familiarity with CI/CD, Git-based workflows, and automated testing.
- Experience collaborating cross-functionally with engineers, analysts, and product managers.
Responsibilities
- Own and evolve our 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.
- Implement testing and observability for analytics pipelines and enforce CI/CD best practices.
- Standardize metric definitions and ensure they are consistently computed across tools.
- Design and maintain Snowflake Cortex semantic views as the governed interface for AI agents.
- Partner with AI/product teams to scope, build, and validate the semantic layer definitions that power internal AI assistants.
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