Senior Analytics Engineer

What you'll do

• Design and build robust dbt models to serve as the foundation for analytics and machine learning features.
• Own and evolve the semantic layer to define metrics, dimensions, and business logic for internal and agentic tools.
• Partner with Engineering and Data Science to ensure the Snowflake data warehouse is well-structured and performant.
• Establish and champion best practices for data modeling, testing, documentation, and code review across the team.
• Collaborate with product teams to scope and deliver native warehouse data delivery to customers.
• Identify and address data quality issues by building observability and governance frameworks.
• Set the standards and patterns for the Analytics Engineering function within the company.

What we're looking for

• 5+ years of experience in analytics engineering, data engineering, or a closely related role.
• Strong command of dbt and SQL.
• Hands-on experience with Snowflake or a comparable cloud data warehouse, including performance tuning and warehouse design.
• Experience building or maintaining a semantic layer or metrics layer.
• Strong knowledge of data modeling fundamentals, including denormalization and slowly changing dimensions.
• Familiarity with data ingestion and CDC tooling.
• Experience establishing standards for testing frameworks, documentation practices, naming conventions, and review processes.
• Must be local to New York City for a hybrid work schedule.
• Experience with native warehouse data delivery or data sharing patterns (preferred).
• Background in fintech, financial services, or a similarly data-intensive regulated industry (preferred).
• Exposure to agentic or LLM-based workflows and the data infrastructure that supports them (preferred).
• Experience with BI tooling such as Looker or Tableau (preferred).