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FIGS

Senior Analytics Engineer

Posted Yesterday
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Hybrid
Santa Monica, CA
130K-150K Annually
Senior level
Easy Apply
Hybrid
Santa Monica, CA
130K-150K Annually
Senior level
Develop and maintain scalable dbt models, dimensional data models, semantic layers, metrics, documentation, tests, and data governance on Snowflake and modern data platforms. Partner with cross-functional stakeholders to define KPIs and deliver trusted self-service analytics. Investigate data quality issues, optimize workloads, improve platform reliability, mentor junior team members, and explore AI-driven workflow automation.
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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.

What You'll Do

Analytics Engineering & Data Modeling

  • 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.

Business Partnership

  • 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.

Data Quality & Reliability

  • 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.

Platform & Process Improvement

  • 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.

What You'll Bring

Required Qualifications

  • 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, BigQuery, 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 requirements gathering through delivery.

Preferred Qualifications

  • Familiarity with experimentation frameworks, customer analytics, marketing attribution, and lifecycle metrics.
  • Experience with BI tools such as Looker, Hex, Secoda AI, etc. 
  • Experience with Python for analytics or data transformation workflows.
  • Knowledge of reverse ETL, customer data platforms (CDPs), and modern data activation strategies.
  • Experience mentoring team members and influencing data strategy across an organization.
  • Demonstrate curiosity and a strong understanding of AI and agentic technologies to elevate data modeling, reliability, and engineering standards.

FIGS Compensation and Benefits

Pay Range

  • At FIGS, your base salary is one part of your total compensation package. This role's base salary range is between $130,000 and $150,000. Actual base salary is determined based on a number of factors, including but not limited to your relevant skills, qualifications, and years of experience. 

Additional Compensation and Benefits 

  • Comprehensive benefits and perks package focused on your well-being, including premium medical, dental and vision coverage, and full access to wellness services through Breethe and Classpass. 100% FIGS-sponsored life insurance and disability insurance  
  • Amazing 401(k) program, with a company match up to the first 6% of your contribution
  • Generous paid time off - We have 12 company holidays. For salaried team members, we offer flexible vacation. For our hourly team members, we offer up to 3 weeks of accrued vacation
  • Meaningful time away for baby bonding, including parental leave, new parent care meals, and a transition back to work for primary caregivers
  • FIGS sponsored Uber Eats voucher for in-office weeks
  • Personalized discount code for 50% off all FIGS products, along with a separate code to share with family and friends to enjoy a 25% discount site-wide
  • Access to FIGS Vet, Discounted Pet Daycare, Discounted Pet Insurance, and so much more…

*Benefits eligibility is determined by hour requirements and length of service 


A little bit about us…

FIGS, Inc. is a founder-led, direct-to-consumer healthcare apparel and lifestyle brand that seeks to celebrate, empower and serve current and future generations of healthcare professionals. We redefine what scrubs are by creating technically advanced apparel and products that feature an unmatched combination of comfort, durability, function and style, all at an affordable price. With the largest DTC platform in healthcare apparel, we sell our products to a rapidly growing community of loyal customers. Through these customer relationships, FIGS has built a community and lifestyle around a profession, revolutionizing the large and fragmented healthcare apparel market and becoming the industry’s category-defining healthcare apparel and lifestyle brand.

Our Threads for Threads initiative is integral to our mission to improve the lives of healthcare professionals on a global scale. Founded alongside FIGS in 2013, Threads for Threads donates scrubs to healthcare professionals working in resource-poor countries around the world. 

FIGS considers all Qualified Applicants, including those with Criminal Histories (e.g., arrests or conviction records), for Employment in accordance with applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.

For information about how we process information in connection with your application, view our Employee & Applicant Privacy Policy linked in the footer below.

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