Lead Analytics Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• Take ownership of the technical architecture and roadmap for our most intricate Analytics Engineering projects, which include designing the semantic layer, consolidating sources of truth, and establishing the data foundation for AI and agent-based applications.

• Design the semantic layer and metrics standards for Forward, ensuring that key business KPIs are defined once, governed clearly, and utilized consistently across dashboards, models, AI agents, and downstream products.

• Spearhead the technical design of the AI-ready data platform, making crucial decisions regarding modeling, metadata, and governance to ensure that Snowflake Intelligence and other AI/agent functionalities are trustworthy, efficient, and production-ready.

• Promote technical excellence within our dbt project by establishing model architecture, materialization and incremental strategies, performance tuning, macros, testing patterns, and CI/CD practices that scale with increasing data volumes and team sizes.

• Set a high standard for craftsmanship across the team, defining SQL style, modeling patterns, documentation, and data quality standards, and exemplifying these standards in your work.

• Mentor Senior and Analytics Engineers through hands-on code reviews, collaboration, and design feedback to accelerate their development into more effective technical contributors.

• Collaborate with the Manager of Analytics Engineering on technical strategy, recruitment, and roadmap planning, acting as a deputy for technical decisions and helping to unblock the team on challenging issues.

• Establish strong technical partnerships with Data Science, Data Engineering, and Core Technology, managing schema migrations, feature deployments, and streaming pipeline contributions where Analytics Engineering is critical.

• Assess and operationalize high-value third-party data sources and emerging tools (e.g., Snowflake Cortex, semantic layer frameworks, observability tools) and provide recommendations that enhance the platform.

• Advocate for data governance and quality at the platform level, including dbt tests, lineage, cataloging, observability, and compliance with security and regulatory standards, ensuring trust in the numbers for both stakeholders and AI systems.

⛳️ Requirements

• A minimum of 6 years of experience in Analytics Engineering, Data Engineering, or Business Intelligence, with a proven track record of leading complex, cross-functional technical initiatives.

• At least 4 years of hands-on experience with dbt in a production environment, including advanced techniques such as incremental strategies, macros, custom tests, and CI/CD design.

• Over 3 years of extensive experience with a cloud-based data warehouse (Snowflake is strongly preferred), with expertise in performance tuning and cost optimization.

• Expert-level skills in SQL and dimensional data modeling, with a portfolio of robust, well-tested models that have served as foundational layers for an organization.

• Proven experience in designing and managing a semantic or metrics layer that acts as an organizational source of truth.

• A demonstrated ability to mentor senior engineers, guide architectural decisions, and influence direction across cross-functional teams.

• Exceptional written and verbal communication skills, capable of fostering technical alignment with both engineers and non-technical stakeholders.

🏝️ Benefits

• Medical

• Dental

• Vision

• A flexible time-off policy

• Paid parental leave

• RRSP match

• Wellness reimbursement

• Volunteering days

• Annual professional development budget

• Charitable donation match