TetraScience leads the R&D Data Cloud space, activating data flow across multiple global pharma and biotech organizations. Scientists worldwide rely on TetraScience’s innovative Tetra Data Platform and Tetra Lab Monitoring applications to accelerate their digital lab transformation. In this role, you will leverage your biology, chemistry, and/or pharmaceutical experience to architect highly impactful solutions and deliver these solutions to our customers in the enterprise pharmaceutical industry and biotech companies.
You will start as a Data Engineer in our Delivery team, owning the prototype and implementation of a customer solution.
What You Will Do
- Research and prototype data acquisition strategy for scientific lab instrumentation
- Research and prototype file parsers for instrument output files (.xlsx, .pdf, .txt, .raw, .fid, many other vendor binaries)
- Design and build data models
- Design and build Python data pipelines, unit tests, integration tests, and utility functions
- Build visualization, report, and dashboards using Spotfire, Tableau, Jupyter notebook and etc.
- Work with the customer to test and make sure the solution fulfills their requirements and solves their need
- Coordinate project kickoff meetings; manage the customer relationship throughout the project, and conduct formal project closeout meetings
- Facilitate internal project post-mortems to identify areas of improvement on the next implementation
During this process, you will work with the Delivery team lead to provide detailed estimates for the number of billable hours per implementation; manage implementation scope, and transform the technical spec into Agile user stories and technical tickets; develop sprint cadence plan for completing the project. You will maintain a project budget to drive decisions and ensure on-time, on-budget, and on-scope delivery. You will also communicate very closely with the rest of the Delivery team, product management, and engineering team to identify potential improvements to the Tetra Data Platform.
As you gain experience as a Data Engineer, you can:
- Take on larger projects that have a more complicated scope
- Take on more platform and product features and continue to grow into a software engineer
Requirements (What You Have Done)
- Proficient with Python and SQL
- Passionate about science and building solutions to make the data more accessible to the end users
Nice to have:
- Elasticsearch, science background or experience with scientific instruments
- Experience with tools like Spotfire, Tableau, Jupyter notebook (any of them)
- Undergraduate or graduate degree in chemistry, biology, computer science, statistics, public health, etc.
- Excellent communications skills, attention to details, and the confidence to take control of project delivery
- Quickly understand a highly technical product and effectively communicate with product management and engineering
- Strong project, account management, and proactive problem-solving skills
- High-bandwidth: thrives when managing multiple simultaneous projects
- Intellectually curious: Unwavering drive to learn and know more every day
- Ability to think creatively on how to solve projects risks without reducing quality
- Team player and ability to "roll up your sleeves" and do what it takes to make the team successful
- 100% employer-paid benefits for all eligible employees and immediate family members.
- Unlimited paid time off (PTO).
- Flexible working arrangements - Remote work + office as needed.
- Company paid Life Insurance, LTD/STD.
- Professional development fund to garner credentials like an AWS Solution Architect certificate