About Joywell Foods

Joywell Foods’ mission is to help people eat better & live better — while still loving their favorite foods.

From 1988 to 2016, US morbid obesity grew from 23% to 40%. The prevalence of sugar in the American food landscape has resulted in more than 100M pre-diabetics/diabetics. Sugar, in all its forms, is among the chief culprits. Joywell is a food technology & consumer goods company that is focused on solving that problem by leveraging precision fermentation to unlock the power of plant-based, sweet proteins in our favorite foods. The result? Far fewer calories, protein-based digestion with no glycolic affect or health unknowns & still, the same great tastes we all love!

Founded by an amazing scientist out of Cal Berkeley, 6-years of R&D under our belts on the cusp of commercialization & backed by top-tier Silicon Valley investor Khosla Ventures, Piva Capital & food-industry investors Evolv & B37 Ventures — Joywell is primed for success. Come join us to help consumers have their cake & eat it too!

Job Description

At Joywell, we are working to build the infrastructure to accelerate our science via data-driven insights. We are seeking an additional Data Engineer to join our group to help build the foundations of this critical data infrastructure. This role is focused on developing cross-functional and cross-organizational data pipelines that accelerate work at the bench and deliver automated insights to the R&D and Executive team. This role will also help administer a SaaS SQL warehouse & LIMS system and provide analytical support to the R&D team. The ideal candidate will have a background in developing fully automated data pipelines using ETL/ELT approaches, specifically leveraging REST APIs. The candidate must also have the ability to work with diverse groups of stakeholders and varying data needs. This position will report to the Director of Data Quality and Analytics and will work very closely with another Data Engineer.

Role & Responsibilities

• Work with R&D staff to develop extract, transform, load (ETL) requirements for individual datasets & instruments
• Work with R&D teams to develop overall data analysis and automation strategies
• Coordinate data-related projects and activities that span the organization to ensure that all high-impact data is captured end-to-end
• Create new database-centric pipelines using ETL/ELT approaches
• Implement analytics workflows and/or data models to support the R&D and Executive teams with valuable insights
• Standardize and improve existing pipelines to adapt to the changing & growing requirements of the start-up environment while adhering to best practices
• Provide continuing support for new and existing data ingestion
• Advise R&D teams on acquisition of new measurement producing equipment, with a focus on data integrations
• Research, recommend and implement additional hardware and software tools

Professional Required Experience & Qualifications

• Fluency in Python & SQL (specifically postgres)
• Experience with data visualization in any tool (Python, R, JMP, Tableau, etc)
• Experience developing fully automated data pipelines
  • Scheduling tasks (cron jobs), polling & events management

Education:

• BS in Computer Science, Data Science, Information Technology, Statistics, Bioinformatics, Computational Biology, or a related field with 2 years of programming experience (within the life sciences preferred, but not required)

Preferred Skills & Experience

• Understanding of bioprocess data and workflows
• Experience and/or understanding of small- to big-data efforts
  • Previous experience with scaling up a pipeline is a huge plus

Personal Characteristics

• Ability to communicate with technical and non-technical audiences
• Enjoys cultivating trust and shared understanding with stakeholders
• Ability to evaluate, learn and embrace new technologies
• Ability to work with diverse team members and technical needs
• Ability to work independently and as part of a small team
• Strong oral, written and collaborative communication skills
• Detail and documentation-oriented
• Flexibility and adaptability to meet the dynamic needs of a startup environment

We want the best people, and we don’t want biases holding us back. We strongly encourage people of every color, orientation, age, gender, origin, and ability to apply. We value a diverse workplace; we prioritize an inclusive climate absent of discrimination and harassment.