Staff Engineer - Experimentation Platform

About the role

You define and execute the long-term strategy for experimentation and measurement across Faire, ensuring company-wide alignment and rigorous standards. You own the design, roadmap, and governance of a centralized experimentation platform powered by Eppo and deeply integrated with Faire's data ecosystem. You establish design patterns and usage guidelines that balance technical leadership with hands-on development in a fast-paced environment. You partner closely with Strategy and Analytics, Product Management, Data Science, and other key stakeholders to translate business objectives into robust experimentation capabilities. You influence adoption and best practices across organizational boundaries while maintaining a focus on scalability, reliability, and developer experience. You champion testability, quality, and observability to build trust in experiment results and support data-driven decisions at scale. You mentor and elevate other engineers by setting clear standards and teaching selected technologies and practices.

Key facts

What you'll do

Define and execute long-term strategy for experimentation and measurement company-wide.

Establish and develop a technology roadmap for a centralized experimentation platform powered by Eppo and integrated with Faire's data ecosystem.

Implement measurement infrastructure, experiment lifecycle, governance, self-service tooling, standards for experiment design, metric creation, and result interpretation.

Partner with Faire's Strategy and Analytics group, Product Management, Data Science, and other functions who are key consumers of experiments infrastructure.

Translate business objectives into experimentation and measurement capabilities that enable teams to make informed decisions.

Implement and operate experimentation platforms, leveraging commercial or open-source solutions with Eppo experience as especially valuable.

Drive strong experiment lifecycle management and apply key methodologies to ensure reliable and interpretable results.

Collaborate across disciplines to enforce rigor, consistency, and trustworthy decision-making throughout the experimentation lifecycle.

Leverage and teach expertise in modern data stacks, with Snowflake and Databricks experience providing particular value.

Utilize and promote expertise in data quality and observability tools, with Anomalo experience especially valuable.

Apply strong SQL skills to design scalable analytical data models that support experimentation at scale.

Select technologies we use and teach, including AWS, Snowflake, Airflow, Spark, Python, and Kotlin, to build a robust experimentation platform.

Requirements

Extensive software engineering experience with a strong focus on experimentation, analytics infrastructure, and product development.

Proficient in defining technical vision for experimentation and leading adoption across organizational boundaries.

Extensive experience designing, building, and scaling experimentation platforms in SaaS systems, with marketplace and e-commerce environments being especially valuable.

Deep understanding of A/B testing, multivariate testing, feature rollout, and progressive delivery techniques.

Ability to translate business objectives into experimentation and measurement capabilities that align with strategic goals.

Experience implementing and operating experimentation platforms, whether commercial or open-source, with Eppo experience holding particular value.

Strong understanding of experiment lifecycle management and key methodologies that ensure validity and reliability.

Experience collaborating across disciplines to ensure rigor, consistency, and trust in experimentation outcomes and decision-making.

Strong knowledge of modern data stacks, with Snowflake and Databricks experience providing particular value in supporting experimentation at scale.

Expertise in data quality and observability tools, with Anomalo experience especially valuable for monitoring experiment data health.

Strong SQL skills and the ability to design scalable analytical data models that support complex experimentation queries and performance.

Select and justify technologies we use and teach, including AWS, Snowflake, Airflow, Spark, Python, and Kotlin, to build and operate a resilient platform.

Practical notes

This role is eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, and location.