Senior Analytics Engineer - CANADA
WFA Digital Insight
As demand for data-driven decision making soars, the role of analytics engineers is becoming increasingly crucial. With the real estate industry undergoing a seismic shift, companies like Luxury Presence are seeking experts who can harness the power of data to drive growth. In this context, the demand for skilled analytics professionals has grown significantly, with a particular emphasis on those proficient in GTM and data modeling. Before applying, candidates should be aware of the company's Series C status and its ambitious plans to hit
Job Description
About the Role
The Senior Analytics Engineer will play a pivotal role in building and scaling the analytical foundation that powers decision-making across key teams at Luxury Presence, including Go-to-Market, Product, Finance, and Operations. This position sits at the intersection of data engineering and analytics, requiring the ability to transform raw data into clean, well-modeled, and trustworthy datasets. The successful candidate will be responsible for ensuring the analytics stack is robust, scalable, and aligned with business objectives, working closely with various stakeholders to achieve this goal.The real estate industry is in the midst of significant change, with technology playing an increasingly important role in how businesses operate and grow. Luxury Presence, backed by prominent investors, is at the forefront of this change, offering a unique AI growth platform designed specifically for real estate professionals. The company's ambition is evident in its rapid growth trajectory, aiming to reach
As a Senior Analytics Engineer, day-to-day responsibilities will involve a mix of technical, strategic, and collaborative work. This includes designing and maintaining the Snowflake data warehouse, ensuring the dbt project is performant and well-documented, and driving data quality and automation across analytics pipelines. The role also involves cross-functional collaboration with Product Management, Marketing, RevOps, Finance, and Engineering teams to ensure the analytics stack meets the needs of various stakeholders.
What You Will Do
- Own and evolve the dbt project, ensuring models are performant, well-tested, and documented.
- Design and maintain the Snowflake data warehouse and ingestion processes.
- Implement modern data modeling best practices to create core entities and datasets that account for complex business processes and logic.
- Drive data quality and automation by implementing 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.
- Act as a 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 by evangelizing best practices in querying, dashboarding, and interpreting metrics, and coach stakeholders toward self-serve.
- Collaborate closely with cross-functional teams to ensure the analytics stack is robust, scalable, and aligned with business objectives.
- Participate in the development of the semantic layer that AI can use to answer stakeholder questions.
What We Are Looking For
- 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.
- Proven experience working with event-based and product usage data.
- Experience connecting marketing data (paid ads, campaigns, attribution) to product analytics, ideally having built end-to-end pipelines from ad platforms through to conversion and retention metrics.
- 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.
- Strong communication and collaboration skills.
Nice to Have
- Proficiency in Python for deeper analysis and automation.
- Experience building and maintaining Airflow DAGs.
- Experience with Spark and PySpark.
Benefits and Perks
- The opportunity to work with a rapidly growing company that is shaping the future of real estate.
- Collaborative and dynamic work environment with a team of experienced professionals.
- Remote work arrangement, providing flexibility and work-life balance.
- Access to cutting-edge technologies and tools.
- Professional development opportunities, including training and education support.
- Competitive compensation package, though specific details are not disclosed.
- Health insurance and other benefits, typical of a remote job.
- The chance to make a significant impact on the company's growth and success.
How to Stand Out
- Ensure you have a strong portfolio showcasing your experience with data modeling, SQL, and dbt.
- Practice explaining complex technical concepts in simple terms, as this is crucial for cross-functional collaboration.
- Be prepared to discuss your experience with data quality and automation, and how you've driven these initiatives in previous roles.
- Highlight your ability to work with large-scale data systems and your familiarity with CI/CD workflows.
- Show enthusiasm for the real estate industry and Luxury Presence's mission, and be prepared to discuss how your skills can contribute to the company's growth.
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