Our Mission
Happiest Baby is a mission-driven company helping parents raise healthy, happy children and saving lives. We created SNOO, the world’s first smart sleeper and the safest baby bed ever made and are also making/developing many more landmark products, content, and services.
SNOO proven to add 1-2 hours of sleep per night and to help protect babies from SIDS (which kills 3500 sleeping babies/year). SNOO has won more top awards than any other baby product, helped hundreds of thousands of parents, is used in over 100 hospitals, is a top benefit at scores of companies, and has been exhibited in six of the world’s top museums (including being invited into the permanent collection of the Smithsonian Institution!).
Happiest Baby was founded by America’s most trusted pediatrician, Dr. Harvey Karp, and his entrepreneur wife, Nina Montée-Karp. Dr. Karp’s celebrated books/videos have helped millions of parents and are translated into over thirty languages. Released in 2016, SNOO is the result of a collaboration between Dr. Karp, award-winning industrial designer Yves Behar (founder of SF-based, Fuseproject) and Dr. Deb Roy (Director, Laboratory for Social Machines, MIT Media Lab).
Role
Happiest Baby is looking for a highly motivated data engineer who is passionate about working on challenging problems in the data infrastructure space. As a data engineer, you will design, build and maintain Happiest Baby’s data lake. In addition, you will support data infrastructure requirements for existing and future products.
Responsibilities:
- Design and implement ETL process for ingesting data from a variety of sources
- Develop tools for monitoring and alerting to maintain high data quality and prevent data loss
- Develop capabilities for data pre-processing and transformation based on data engineering best practices
- Build and maintain data pipelines that support analytics, dashboards and reporting
- Work with data scientists and engineers to set up infrastructure to deploy AI models
- Implement solutions to monitor data compliance
- Work cross-functionally with marketing, product and operations teams to support data infrastructure needs
- Stay up to date with advances in data engineering and suggest infrastructure improvements and tools for optimizing data processes and pipelines
Required Qualifications:
- Bachelor’s degree in Computer Science, Data Science, Mathematics or a related field
- 2+ years of industry experience with data lake/data warehouse building ETL/ELT pipelines
- Experience working with cloud technologies such as AWS, GCP
- Proficient in Python, SQL
- Experience working with big data processing frameworks such as Postgres, Apache Spark, MapReduce etc.
- Working knowledge of SQL and NoSQL databases such as MongoDB, Elasticsearch
- Strong data visualization skills
Preferred Qualifications:
- Master’s degree in Computer Science, Data Science, Mathematics or a related field
- Hands on experience using AWS S3, Glue, Redshift, Google BigQuery for data transformation and processing
- Experience building infrastructure to run large scale machine learning algorithms
- Experience working with video data ingestion and processing
- Ability to communicate technical details in a concise manner to stakeholders
Perks
- Competitive health/dental/eyecare plan
- 401(k) plan
- Daily catered lunches
- Take-what-you-need vacation
- Dog-friendly environment
- Indoor-outdoor workspace
- Working with a great team that is literally saving babies’ lives!