Senior Staff Data Engineer - Platform Data and Analytics
Faire · Anywhere in the World · Remote
Faire
Faire operates an online wholesale marketplace connecting independent retailers with brands and makers, using data and machine learning to modernize a historically offline, fragmented industry. Founded in San Francisco in 2017 by former Square employees, it has grown into a major player in B2B wholesale commerce, competing with players like Tundra, Abound, and traditional trade shows, while attracting significant venture backing and a valuation among the more prominent marketplace startups to emerge in recent years. Its platform offers retailers curated product discovery, net payment terms, and free returns on first orders, while giving brands access to a global network of independent shops without the overhead of traditional wholesale distribution.
Gig description
Headquarters: Remote - US 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. Note: This is a remote role open to candidates located in Arizona, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Illinois, Indiana, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, Ohio, Oregon, Pennsylvania, Rhode Island, Tennessee, Texas, Utah, Virginia, Washington, or Wisconsin. 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 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. Excellent communication, leadership, and influencing skills. A bachelor's degree in Computer Science/Software Engineering or equivalent industry experience. Select technologies we use and teach : AWS, Snowflake, Airflow, Spark, Python, Kotlin. Salary Range California & New York: the pay range for this role is $276,000 to $379,500 per year. 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. The base pay range provided is subject to change and may be modified in the future. Faire uses Artificial Intelligence (AI) to screen and select applicants for this position. This job posting is for an existing vacancy. 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. Why you’ll love working at Faire Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly. Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day. Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours. Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work. Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success. Faire was founded in 2017 by a team of early product and engineering leads from Square. We’re backed by some of the top investors in retail and tech including: Y Combinator, Lightspeed Venture Partners, Forerunner Ventures, Khosla Ventures, Sequoia Capital, Founders Fund, and DST Global. We have headquarters in San Francisco and Kitchener-Waterloo, and a global employee presence across offices in Toronto, London, and New York. To learn more about Faire and our customers, you can read more on our blog . 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. We will work with all applicants to accommodate their individual accessibility needs. To request reasonable accommodation, please fill out our Accommodation Request Form ( https://bit. ly/faire-form) Privacy 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 (https://www. faire. com/privacy) To apply: https://weworkremotely. com/remote-jobs/faire-senior-staff-data-engineer-platform-data-and-analytics
Requirements to meet
Disclaimer
Suggestions only — review each course yourself to judge whether it meets the role's requirements. Completing a course doesn't guarantee proficiency or that you'll qualify; hiring standards vary by employer.
Skills required
Machine Learning (required)
GapCourses that may help you meet this requirement:
Make data available in Azure Machine Learning
Microsoft Learn · beginner · Free · 39m · ★ 4.8
This beginner course directly addresses the Machine Learning skill gap for the Data Engineer role by covering core machine learning concepts through making data available in Azure Machine Learning.
Introduction to DevOps principles for machine learning
Microsoft Learn · beginner · Free · 33m · ★ 4.7
This course directly covers Machine Learning, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 1 hours.
Continuous deployment for machine learning
Microsoft Learn · beginner · Free · 22m · ★ 4.7
This course directly covers Machine Learning, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 0 hours.
Python (required)
GapCourses that may help you meet this requirement:
PySpark & Python: Hands-On Guide to Data Processing
Coursera · beginner · $49/mo · 5h · ★ 4.4
This course directly covers Python, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 5 hours.
Data Analysis with Python
freeCodeCamp · beginner · Free
This course directly covers Python, which appears as a requirement in the Data Engineer posting at a beginner level.
Pandas
Kaggle Learn · beginner · Free
This beginner Pandas course helps build Python proficiency, a key skill required for the Data Engineer role.
SQL (required)
GapCourses that may help you meet this requirement:
Explore data roles and services
Microsoft Learn · beginner · Free · 22m · ★ 4.8
This course covers SQL, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 0 hours.
Combine multiple tables with JOINs in T-SQL
Microsoft Learn · beginner · Free · 1h · ★ 4.8
This beginner course builds core SQL skills by teaching how to combine multiple tables with JOINs in T-SQL, directly addressing the SQL skill gap for the Data Engineer role.
Explore fundamental relational data concepts
Microsoft Learn · beginner · Free · 37m · ★ 4.8
This course covers SQL, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 1 hours.
AWS (required)
GapCourses that may help you meet this requirement:
AWS Fundamentals Specialization
Coursera · beginner · $49/mo · 40h · ★ 4.8
This course covers AWS, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 40 hours.
AWS Cloud Technical Essentials
Coursera · beginner · $49/mo · 20h · ★ 4.8
This course covers AWS, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 20 hours.
AWS Cloud Solutions Architect Professional Certificate
Coursera · intermediate · $49/mo · 62h · ★ 4.8
This course covers AWS, which appears as a requirement in the Data Engineer posting at an intermediate level and can be completed in approximately 62 hours.
Analytics (required)
GapCourses that may help you meet this requirement:
Explore concepts of data analytics
Microsoft Learn · beginner · Free · 15m · ★ 4.8
This course directly covers Analytics, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 0 hours.
Integrate data with Azure Data Factory
Microsoft Learn · beginner · Free · 1h · ★ 4.6
This course covers Analytics, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 1 hours.
Data Analysis with Python
freeCodeCamp · beginner · Free
This course covers Analytics, which appears as a requirement in the Data Engineer posting at a beginner level.
Product Management (required)
GapCourses that may help you meet this requirement:
Digital Product Management: Modern Fundamentals
Coursera · beginner · $49/mo · 10h · ★ 4.7
This course directly covers Product Management, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 10 hours.
Product Management: An Introduction
Coursera · beginner · $49/mo · 20h · ★ 4.6
This course directly covers Product Management, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 20 hours.
Generative AI for Product Managers Specialization
Coursera · intermediate · $49/mo · 36h · ★ 4.7
This course covers Product Management, which appears as a requirement in the Data Engineer posting at an intermediate level and can be completed in approximately 36 hours.
Spark (required)
GapCourses that may help you meet this requirement:
Spark and Python for Big Data with PySpark Specialization
Coursera · beginner · $49/mo · 30h · ★ 4.6
This course directly covers Spark, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 30 hours.
Use Apache Spark in Microsoft Fabric
Microsoft Learn · intermediate · Free · 1.5h · ★ 4.8
This course directly covers Spark, which appears as a requirement in the Data Engineer posting at an intermediate level and can be completed in approximately 1 hours.
Use Apache Spark in Azure Databricks
Microsoft Learn · intermediate · Free · 1.5h · ★ 4.7
This course directly covers Spark, which appears as a requirement in the Data Engineer posting at an intermediate level and can be completed in approximately 1 hours.
Airflow (required)
GapCourses that may help you meet this requirement:
ETL and Data Pipelines with Shell, Airflow and Kafka
Coursera · intermediate · $49/mo · 17h · ★ 4.5
This course directly covers Airflow, which appears as a requirement in the Data Engineer posting at an intermediate level and can be completed in approximately 17 hours.
Apache Airflow Best Practices
Coursera · intermediate · $49 · 10h
This course directly covers Airflow, which appears as a requirement in the Data Engineer posting at an intermediate level and can be completed in approximately 10 hours.
Snowflake (required)
GapCourses that may help you meet this requirement:
Intro to Snowflake for Devs, Data Scientists, Data Engineers
Coursera · beginner · $49/mo · 12h · ★ 4.8
This course directly covers Snowflake, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 12 hours.
Snowflake - Introduction Course
Coursera · beginner · $49 · 4h · ★ 4.5
This course directly covers Snowflake, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 4 hours.
Building AI Agents with Snowflake
Coursera · intermediate · $49/mo · 5h · ★ 4.8
This course directly covers Snowflake, which appears as a requirement in the Data Engineer posting at an intermediate level and can be completed in approximately 5 hours.
ETL (required)
GapCourses that may help you meet this requirement:
Explore data roles and services
Microsoft Learn · beginner · Free · 22m · ★ 4.8
This course covers ETL, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 0 hours.
The Path to Insights: Data Models and Pipelines
Coursera · advanced · $49/mo · 17h · ★ 4.7
This course covers ETL, which appears as a requirement in the Data Engineer posting at an advanced level and can be completed in approximately 17 hours.
Integrate data with Azure Data Factory
Microsoft Learn · beginner · Free · 1h · ★ 4.6
This course covers ETL, which appears as a requirement in the Data Engineer posting at a beginner level and can be completed in approximately 1 hours.