New York, NY
We are the first sleep fitness company. We design products at the forefront of sleep innovation. Our mission is to fuel human potential through optimal sleep. We use innovative technology, detailed design, and proven science and data to personalize and improve each night for everybody—changing the way people sleep forever and for better.
Backed by leading Silicon Valley investors including Founders Fund, Khosla Ventures and Y Combinator, we’ve raised 68 million to date. We were recognized as one of Fast Company’s Most Innovative Companies in Consumer Electronics in 2018.
Our temperature-regulated smart bed, the Pod is an absolute game changer, improving people's health and happiness by changing the way they sleep. It was named one of Time Magazine’s Best Inventions of 2019. We’re excited by the recognition and still have a long way to go toward achieving our mission.
That's why we are looking for our first Data Engineer to help launch a new business intelligence effort. This role will largely focus on data pipeline and data warehouse issues while also supporting advances in customer lifecycle marketing, business intelligence platform, customer lifetime value, customer segmentation, web and mobile app user flow, on-site creative analysis, A/B testing, etc.
We are seeking someone who is passionate about designing, implementing, and supporting an analytical data infrastructure that provides ad-hoc access to large datasets and computing power in an entrepreneurial environment. The ideal candidate also has a passion for health tech and wellness.
How you'll contribute:
- Join the Lead Data Engineer to strategize and execute a data architecture and infrastructure to meet business objectives
- Define and implement technical requirements, technical and data architectures for the data warehouse
- Lead designs and implementations in order to meet quality, performance, scale, and manageability requirements
- Design and manage the ETL process, including data quality and testing
- Design and manage the information access and delivery effort for the data warehouse
- Maintain high bar for data quality and understand the data needs our various source data in order to anticipate and scale our systems
- Own and proactively support what you put into production
What you'll need to succeed:
- 3+ years’ experience deploying production ready data warehouse, AI, ML, and reporting tools (e.g. Snowflake, Redshift, BigQuery, H2O.ai, OpenAI, Microsoft AI, Jupyter, Looker, etc.)
- An excellent understanding of computer programming, database schema design, and engineering best practices
- Ability to quickly establish solutions and take advantage of ML/AI technologies
- Experience in data warehouse environments and hands-on knowledge of cloud-based infrastructure (AWS) is desired
- Experience with Spark
- Understanding of Python, Node with Typescript, and more
- Understanding of BigQuery or other SQL engines such as Hive, Impala, Athena, or Presto
- Understanding of object stores such as S3 and GCS
- Experience with Docker and Kubernetes or AWS ECS
- Bachelors in Computer Science, Engineering or equivalent experience
- Experience in the healthcare, wellness, and/or eCommerce / retail company or have familiarity with health data and eCommerce trends and best practices
Why you'll love working here:
- We’re a tight-knit, passionate team that’s working to improve people’s lives by improving the way they sleep
- Leadership is committed to employees’ wellness and career development
- You’ll get a better night sleep every night; all full-time employees receive the Pod
- Flexible, generous PTO
- 100% employer contribution for medical/dental/vision insurance
- Discounted gym memberships, commuter benefits
- Weekly team happy hours and lunches
- Office snacks
We continually celebrate the diverse community different individuals cultivate. As an equal opportunity employer, we stay true to our values by ensuring everyone feels they can flourish and grow. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.