Senior Staff Data Engineer - Platform Data and Analytics

About Faire

Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive.

We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.

About this role

Our Engineering organization owns the software that makes our marketplace work. The Platform group empowers teams across Faire: Product Engineering, Data Science, Product Management, Strategy, Analytics, Finance, etc. Enabling these functions to do their best work without concern about underlying infrastructure. We enable product engineering teams to build and operate software with unmatched speed and quality. We care about good engineering practices, excellent developer experience, security, testability, ease of maintenance, and scaling to serve millions of users. We value best practices to achieve excellent availability and performance.

This role is for a highly experienced technical leader in the data space, whose influence spans multiple Platform and Product groups.

Within the Platform group:

• The Data Infrastructure team builds and operates a secure, reliable, cost-efficient, opinionated platform for data ingestion, storage, compute, orchestration, and governance.
• The Analytics Platform team builds efficient data warehousing capabilities, foundational data assets, and tools to accelerate data-driven analytics. Its mandate is to reduce time from data to insights.

The teams also own relationships with relevant technology infrastructure vendors.

Additionally, this role would influence and interact with all data and analytics related functions at Faire. The product analytics engineering (PAE) function enables domain-specific AE capabilities, working closely with Data Science, Strategy & Analytics, Finance. The data science (DS) function leads modeling development and evaluation, raising effectiveness and efficiency of key product features.

We’re looking for:

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.

What you’ll do

• 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, monitoring, alerting, and cost tracking for workloads, design practices for foundational assets, data security, privacy, and governance.

Qualifications

• Experience designing, developing, and operating data streaming, batch, ETL/ELT, orchestration, storage, compute, workflow systems at scale.
• Experience defining architecture patterns and building reliable, scalable data pipelines, orchestration of data movement, querying, transformation, and frameworks for analytics engineering workflows.
• Strong SQL and Python skills and experience.
• Data warehousing experience at Petabyte scale.
• Snowflake, Airflow, Spark experience especially valuable.
• Understanding of performance, capacity, cost trade-offs in data processing systems. Experience in guiding technical and product teams on such trade-offs.
• Experience diagnosing, mitigating, and per