- San Francisco
- Date Posted
- Jun. 2, 2021
- Data Science
Our mission is to make buying online faster, safer and easier for everyone. Fast Login and Fast Checkout enable a one-click sign-in and purchasing experience that makes it easier for people to buy and merchants to sell. The company’s products work on any browser, device or platform to deliver a consistent, stress-free purchasing experience. Fast is entirely consumer-focused and invests heavily in its users’ privacy and data security. Headquartered in San Francisco but open to globally remote, we are a founders-led, privately held company funded by Stripe, Index Ventures, Susa Ventures and other world-class investors.
We are committed to diversity and inclusion, and demonstrate our values through equitable pay, fantastic benefits, and access to all reasonable accommodations.
As a Data Engineer at Fast, you will write data solutions, transform, and optimize large sets of raw and processed data, and implement data architectures used at Fast to support our product features. You would optimize data flow and representation to be consumed by distributed systems, reporting, analytics and machine learning, and will work closely with the engineering teams to architect solutions that enable robust and scalable data access and analysis.
- Interface with engineers, product managers and machine learning scientists/engineers to understand data needs and implement robust and scalable solutions
- Work directly with DS scientists/engineers to implement robust and reusable data models
- Build out automated solutions for ML feature testing, validation, and release
- Implement and maintain a data version control system
- Enable automated data preparation for model training
- Ensure data quality and accessibility for all types of data used at Fast
- Design, build, enhance, and launch ETL processes for new and existing data sources
- Augment existing data with output from machine learning analysis/algorithms
- Systematically identify and rectify data quality issues (missing data, mislabeled, old, poor schema/model, etc)
- Produce basic statistical analyses and visualizations to help guide product and business decisions
- Bachelor’s degree in a technical field (computer science, engineering, mathematics, informatics); advanced degree preferred (or equivalent experience)
- 4+ years of industry data engineering experience, including experience in ETL design, implementation and maintenance
- Proven experience in the data warehouse space, as well as schema design and dimensional data modeling
- Profound knowledge of SQL and python
- Practical application of basic statistical methods
- Basic experience working on machine learning projects
- Prior working experience with FinTech, payments, identity, and wearable devices
- Data visualization skills (R, python, Tableau)
- Familiarity with tools for analysis of very large datasets
Benefits of life @ Fast
- Fast Flex allows all of our employees to choose where they want to work: our office (when open), their home or any place else in the world.
- Early stage well-funded company with innovative engineering and product culture
- Inclusion and diversity as a company priority
- Competitive compensation packages
- Comprehensive benefits (including 99% of healthcare cost and 401k matching)
- Home office reimbursements and snack deliveries (and awesome swag!)