Solutions Architect developing scientific informatics solutions on Dotmatics LUMA platform. Collaborating with product teams and external stakeholders to enhance lab automation and workflows.
Responsibilities
Develop configuration: Create registration entities, data flows, task templates, data visualization experiences, and other configurations in support of developing Luma Solutions that will be delivered as part of the product
Test and troubleshoot configuration: Perform in-team testing of configuration and assist is handing test cases to the QA group for release testing. Troubleshoot configuration to understand why it is not producing desired results.
Contribute to documentation: Write draft documentation of configuration and workflows and collaborate with the Documentation team to develop final customer-facing documentation
Train internal and external users: Train members of other Dotmatics teams and early customers on how to use Luma Solutions configuration and the workflows it supports
Champion quality and best practices: Actively participate in the development of best practices for Luma configuration, and ensure these best practices are followed in the development of Luma Solutions.
Provide input into new product features: Use new product features in Luma Solutions and provide feedback on the experience, participate in user experience testing, and provide input to the Product team about features that will enable the best Solutions
Provide input into the Solutions roadmap: Prototype ideas for new Solutions capability and provide input on how the prototypes can inform the Solutions roadmap
Requirements
3+ years experience developing informatics solutions for Life Sciences customers
Understanding of data models and how they influence configuration options
Experience configuring low-code software
Demonstrated success working on scientific data platforms or tools involving data modeling, ETL, APIs, and BI/reporting
Strong SQL skills required
Passion for quality and continuous improvement—driven by a desire to solve meaningful problems
Bachelor's or advanced degree in Life Sciences, Data Science, Chemistry, Biology, Bioinformatics, or related technical discipline
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