Senior Analytics Engineer

FIGS is seeking a highly motivated Senior Analytics Engineer to join our Data Engineering team. This role sits at the intersection of data engineering, analytics, and business strategy, transforming raw data into trusted, scalable data products that power decision-making across the organization.

As a Senior Analytics Engineer, you will own the development of curated datasets, semantic models, and analytics frameworks that enable teams across Product, Marketing, Operations, Finance, Supply Chain, and Ecommerce to self-serve insights confidently. You will partner closely with Data Engineers, Analysts, and business stakeholders to define data standards, improve data quality, and build scalable analytics solutions.

The ideal candidate combines strong technical expertise in modern data platforms with a passion for translating business needs into reliable, well-documented data assets.

• Design, develop, and maintain scalable dimensional data models and semantic layers that support reporting, experimentation, and advanced analytics.
• Build, refactor, and maintain production dbt models in Snowflake, including staging, intermediate, mart, incremental, snapshot, and semantic/metrics layers.
• Develop reusable data products, metrics definitions, and business logic to ensure consistency across reporting and analysis.
• Establish and maintain data lineage, documentation, testing, and governance practices.

• Collaborate with stakeholders across Ecommerce, Marketing, Finance, Operations, Product, and Customer Experience to understand analytical requirements and translate them into scalable solutions.
• Drive alignment on KPI definitions, metric governance, and reporting standards.
• Partner with analysts and business teams to improve self-service analytics capabilities.

• Implement automated testing, monitoring, and validation processes to ensure high-quality data assets.
• Investigate and resolve data discrepancies, pipeline failures, and reporting inconsistencies.
• Define and champion best practices for analytics engineering, documentation, and code review.

• Contribute to the architecture and evolution of FIGS' modern data stack.
• Optimize Snowflake and dbt workloads for performance, scalability, and cost efficiency, including query tuning, materialization strategy, warehouse usage, and incremental model design.
• Mentor analysts and junior team members on data modeling, SQL development, and analytics engineering best practices.
• Optimize data platforms by identifying opportunities for AI and agentic technology integration, automating complex workflows to improve efficiency, scalability, and system stability.

• 5+ years of experience in Analytics Engineering, Data Engineering, Business Intelligence, or related data roles.
• Experience in Ecommerce, Retail, Consumer Products, or DTC businesses.
• Advanced SQL skills with experience building production-grade data models.
• Hands‑on experience architecting dbt projects, including model layering, naming conventions, tests, documentation, macros, packages, exposures, and deployment workflows.
• Experience working with modern cloud data warehouses such as Snowflake, Big Query, Databricks, or Redshift.
• Strong understanding of dimensional modeling, data warehousing concepts, and analytics best practices.
• Experience with Git‑based analytics workflows, dbt testing, code review, deployment processes, and data quality checks.
• Strong ability to investigate data quality issues across source systems, transformation logic, and BI outputs.
• Ability to communicate complex technical concepts clearly to both technical and non‑technical audiences.
• Ability to independently drive projects from…