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 use 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 we can level the playing field so businesses can grow and local communities can thrive. 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.

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 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. 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‑productive 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.

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. Understanding of performance, capacity, cost trade‑offs in data processing systems.

Experience guiding technical and product teams on such trade‑offs.

Experience diagnosing, mitigating, and permanently addressing data system production issues at scale.





Experience rolling out patterns for workload performance and cost optimization.

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. A bachelor’s degree in Computer Science/Software Engineering or equivalent industry experience.

AWS, Snowflake, Airflow, Spark, Python, Kotlin. This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location.

Hybrid

Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in‑office roles will have the flexibility to work remotely up to 4 weeks per year.

Specific

Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting. Faire uses Artificial Intelligence (AI) to screen and select applicants for this position. Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.

Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire’s Privacy Notice. #

📌 Senior Staff Data Engineer - Platform Data and Analytics (Toronto)
🏢 Faire
📍 Toronto