Senior Staff Data Engineer (Platform Data and Analytics)

Join Faire, a fast-growing marketplace, as a Senior Staff Data Engineer. In this role, you will lead the architecture development of our data infrastructure, engage in team planning and prioritization, and provide technical guidance and mentorship. You will work closely with various teams across the organization, including Product Engineering, Data Science, Product Management, Strategy, Analytics, and Finance. This position offers comprehensive healthcare benefits, generous time off, parental leave, productivity support, and opportunities for personal and professional development.

• Plan and execute on technology projects that scale with Faire’s growth; lead architecture development with a focus on data integrity, security, performance, scale, reliability, monitoring/alerting.
• Engage with team planning and prioritization, balancing urgent and near-term needs with long-term goals.
• Provide technical guidance and mentorship on the most difficult open-ended problems we face. Including cost-efficient compute and storage, ETL and ELT pipelines, data ingest and warehousing.
• This role is for a highly experienced technical leader in the data space, whose influence spans multiple Platform and Product groups
• An experienced technical leader with data and analytics background to work alongside and lead / influence across multiple teams and departments. Define technology strategy, roadmaps, architecture patterns and guidance. Striking the right balance of technical leadership and hands-on development
• Select technologies we use and teach: AWS, Snowflake, Airflow, Spark, Python, Kotlin
• Experience defining architecture patterns and building reliable, scalable data pipelines, orchestration of data movement, querying, transformation, and frameworks for analytics engineering workflows
• Understanding of performance, capacity, cost trade-offs in data processing systems. Experience in guiding technical and product teams on such trade-offs
• Experience designing, developing, and operating data streaming, batch, ETL/ELT, orchestration, storage, compute, workflow systems at scale
• A bachelor's degree in Computer Science/Software Engineering or equivalent industry experience
• Experience operating in a growth stage company, with a data function consisting of multiple teams and over 60 people. Enabling teams to operate in a self-serve model
• Data warehousing experience at Petabyte scale
• Experience diagnosing, mitigating, and permanently addressing data system production issues at scale. Experience rolling out patterns for workload performance and cost optimization
• Snowflake, Airflow, Spark experience especially valuable
• Excellent communication, leadership, and influencing skills
• Strong SQL and Python skills and experience