Software Data Architect

  • Joyn Bio
  • Remote, USA
  • Jul 28, 2020

Job Description

Joyn Bio is a joint venture between Bayer and Ginkgo BioWorks dedicated to addressing unmet needs in agriculture by applying synthetic biology approaches to engineer microbes.


  • Drive the design and development of Joyn’s cloud native tools that optimize the acquisition, storage, integration, and facilitate machine learning of biological data.


  • Design, build, test, learn to create machine learning solutions.  You are part strategic leader (architect) and part doer (engineer) who will develop tools to enable the data management of Joyn Bio’s R&D pipeline.  As an architect, you will canvas SMEs to understand problems, requirements, data flow & usage, and work processes. You will design different solutions, creating an end-to-end view of how these fit with Joyn’s primary information needs. You will create a solution roadmap with milestones, timelines that aligns with the dept head’s vision.  As a leader you are not afraid to make build vs. buy decisions. Recognizing the need in a small startup to have all hands on deck and iterate quickly, you are ready to dive in and work as an engineer and build data models, databases, integrate analytical tools (JMP, RStudio, Jupyter Notebooks), create data microservices, and manage the related infrastructure.
  • Participate in the full development cycle:  Provide leadership on the introduction of new data products and product modifications from inception, research, prototyping to release in production.  You embrace and promote agile development principles and best practices for software development. You will drive automated testing, especially with various dependencies across the organization and partners making sure that operations on exchanged data work as expected, and fail loudly when they don't. As a leader, you demonstrate strong technical and thought leadership and ability to influence and guide the work of others.  As an outward-looking visionary you admit the limits of your technical knowledge and look to others to learn and embody their hard-fought lessons.
  • Ginkgo Interface and Joyn’s Value Proposition:  You will work collaboratively with Gingko’s computational teams to understand the Ginkgo data and software ecosystem to ensure complementarity of software solutions, leverage know-how, execution and expertise in Ginkgo’s developing innovative research platforms.  In addition, you will engage with different technology partners to facilitate the build of Joyn’s analytical ecosystem.
  • Create a data-centric culture: You will be able to communicate stories of how data models, architecture and analytics impact the business. Working with the Dept head to enable IP, trade secret and compliance for regulatory aspects, you will build a transparent and traceable data supply chain that enables reverse data lineages.  Long term you and your team will be the organization’s trusted data advisor, responsible for the entire data modeling ecosystem including data lineages, master data and metadata management, common data structures & formatting, data quality, governance and standards.


  • 5-10 years of industry experience in software building machine learning platforms - expertise in at least 1 languages required - Python, Java, etc.
  • Experience with AWS services.
  • Experience in building relational, graph (e.g. Neo4J).
  • Should have a proven track record of collaborating, developing and building data architecture in a compliant environment.
  • BS or MS in Computer Science, engineering or relevant field.
  • Prior supervisory experience in leading teams of 2-5 people is required.
  • A passion for creating transformative agricultural products, discovering new ways to add value to farmers.


  • This position reports to the Head of Computational Biology and Data Science.
  • This position will be a part of the Platform and Infrastructure team and will interact with cross-disciplinary and multiple program teams.
This position is Remote based.

Organization type



51-200 employees  


Food & Agriculture

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