Analytics Engineer
About Faire
Faire is an online wholesale marketplace built on the belief that the future is local — there are over 2 million independent retailers in North America and Europe doing more than $2 trillion in revenue. 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 that small businesses everywhere can compete with these big box and e-commerce giants.
By supporting the growth of independent businesses, Faire is driving positive economic impact in local communities, globally. 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.
Job Description - Analytics Engineer
The Data Infrastructure team is the backbone of all data-related processes and enables the Data Science team to develop and deploy a wide variety of algorithms and models that power the marketplace. Our infrastructure is used by the whole company for analytics, reporting, forecasting and research. We care about having a reliable infrastructure with quality data and building machine learning models that help our customers thrive.
As an Analytics Engineer you’ll be responsible for developing and automating large scale, high-performance data storage and processing systems.
Our team already includes experienced Data Scientists and Engineers from Airbnb, Facebook, Quora, Square, Uber, and Pinterest. Faire will soon be known as a top destination for data science and machine learning, and you will help take us there!
What it takes:
- 1+ years experience in a Data Engineering or Analytics role managing data pipelines
- Strong skills in Python, SQL, Airflow, Data Modeling and ETL pipelines
- Familiarity with: Snowflake, AWS Redshift, or BigQuery
- Experience working with Data Science and Machine Learning teams as stakeholders
- A passion for programming and solving problems with code
- A bachelor's degree in Computer Science/Software Engineering or equivalent industry experience
- A love for technology, and an insatiable curiosity for new tools to tackle real problems
Why you’ll love working at Faire
- We are entrepreneurs: Faire is being built for entrepreneurs, by entrepreneurs. We believe entrepreneurship is a calling and our mission is to empower entrepreneurs to chase their dreams. Every member of our team is an owner of the business and taking part in the founding process.
- We are using technology and data to level the playing field: We are leveraging the power of product innovation and machine learning to connect brands and boutiques from all over the world, building a growing community of more than 350,000 small business owners.
- We build products our customers love: Everything we do is ultimately in the service of helping our customers grow their business because our goal is to grow the pie - not steal a piece from it. Running a small business is hard work, but using Faire makes it easy.
- We are curious and resourceful: Inquisitive by default, we explore every possibility, test every assumption, and develop creative solutions to the challenges at hand. We lead with curiosity and data in our decision making, and reason from a first principles mentality.
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 Salt Lake City, Atlanta, Toronto, London, New York, LA, and Sao Paulo. 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.