Lead Analytics Engineer

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

📋 Description

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

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

• Direct the technical design of the AI-ready data platform by making decisions regarding modeling, metadata, and governance that ensure Snowflake Intelligence and other AI/agent functionalities are reliable, efficient, and ready for production.

• Promote technical excellence within our dbt project through model architecture, materialization and incremental strategies, performance optimization, macros, testing practices, and CI/CD methods that can scale with increasing data volume and team size.

• Establish and maintain high standards for craftsmanship within the team, defining SQL style guidelines, modeling patterns, documentation requirements, and data quality expectations, while exemplifying these standards in your own work.

• Provide mentorship to Senior and Analytics Engineers through hands-on code reviews, collaborative work, and design feedback, thereby accelerating their development as stronger technical contributors.

• Collaborate with the Manager of Analytics Engineering on technical strategy, recruitment, and roadmap planning, serving as a deputy for technical decisions and helping to resolve the most challenging issues faced by the team.

• Foster deep technical partnerships with Data Science, Data Engineering, and Core Technology teams, taking ownership of schema migrations, feature deployments, and contributions to streaming pipelines where Analytics Engineering plays a critical role.

• 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, encompassing dbt tests, lineage, cataloging, observability, and compliance with security and regulatory standards, ensuring that both stakeholders and AI systems can rely on the data.

⛳️ Requirements

• Over 6 years of experience in Analytics Engineering, Data Engineering, or Business Intelligence.

• More than 4 years of hands-on experience with dbt in production, including advanced practices like incremental strategies, macros, custom tests, and CI/CD design.

• At least 3 years of extensive experience with a cloud-based data warehouse, preferably Snowflake, focusing on performance tuning and cost optimization.

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

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

• Demonstrated capability to mentor senior engineers, guide architectural decisions, and influence direction across cross-functional teams.

• Exceptional written and verbal communication skills, enabling effective technical alignment with both engineers and non-technical stakeholders.

🏝️ Benefits

• 12% Annual Target Bonus

• Fair and transparent compensation