Senior Data Engineer
Summary
Build and maintain a privacy-focused data platform in Snowflake using dbt and Dagster, enabling accurate KPI tracking and analytics for a digital banking business.
Senior Data Engineer at relayfi. About the role Relay is a digital banking platform designed to provide business owners with financial clarity and control. We are looking for a Senior Data Engineer to scale our data ecosystem and ensure our teams have access to high-quality, timely information to support company growth.
Location: Toronto, ON (Hybrid) Engagement: Full-time Compensation: $144,000 - $176,000 CAD (Target starting salary: $160,000 CAD) Team: Engineering
What you’ll do
- Develop and maintain dbt models within Snowflake to support privacy-focused data analysis.
- Manage and improve the systems and processes that form our data platform.
- Build infrastructure to track key performance indicators and ensure data availability across the organization.
- Collaborate with stakeholders to design systems that provide accurate data for business operations.
- Partner with Trust, Security, and Governance teams to maintain high standards for customer data safety.
Requirements
- Minimum 3 years of professional experience in Data Engineering.
- Advanced SQL proficiency, including complex window functions, schema design, and query optimization.
- Fluency in Python with a focus on writing clean, production-ready code.
- Hands-on experience with dbt, Dagster, Snowflake, and cloud infrastructure (AWS, GCP, or Azure).
- Experience working with BI and data visualization tools like Looker, Metabase, or Mode.
- Ability to work independently while collaborating effectively with cross-functional teams.
Nice to have
- Proficiency in applied statistics and the creation of quantitative models.
- Domain expertise in SaaS or banking analytics, specifically regarding LTV, churn, and retention.
- Experience with microbatch or streaming analytics (Spark Streaming, Flink, Beam) and event stores (Kafka, Kinesis, PubSub, Pulsar).
- Background in scaling data systems at early-stage companies.
Skills & tools
SQL, Python, dbt, Dagster, Snowflake, AWS/GCP/Azure, BI tools (Looker/Metabase/Mode).
Practical notes
- The interview process includes a 30-minute talent screen, a 45-minute technical deep dive, a 60-minute case study presentation, and a 45-minute in-person leadership interview.
- Offers are based on impact and readiness, with no fixed annual review cycle for compensation adjustments.
- Employment is conditional upon a successful background check and verification via Certn.
- Accommodations are available upon request during the hiring process.