Senior Data Engineer
DemandbaseSalary not specified
Full Time
Senior (5 to 8 years)
Not SpecifiedCompensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Scientific Data, AI Cloud, Lab Data Management, Scientific AIIndustries
Requirements
Candidates should possess over 5 years of experience developing distributed systems for collecting and processing large datasets. Proficiency in Node.js, Typescript, or Python, along with databases and SQL, is required. Familiarity with data visualization tools like Streamlit or Plotly Dash, container technologies such as Docker, and cloud infrastructure providers (AWS, Azure, GCP) is necessary. Experience with writing maintainable unit and automated integration tests, strong application debugging skills, and excellent communication and technical writing abilities are also essential. A Bachelor's or Master's degree in Computer Science or a relevant scientific field is required, with experience in Life Sciences or scientific data being a significant advantage.
Responsibilities
The Software Engineer will join the Tetra engineering team to build infrastructure supporting scientific analysis software. They will be responsible for self-starting and making progress in ambiguous situations, designing and developing efficient platforms and tools for scientific analysis software development and deployment. The role involves addressing resiliency, scale, and high availability requirements for these tools, delivering a high-quality product using agile methodologies, and partnering with the product management team to bring visions to life. The engineer will also work with a geographically dispersed team, represent their positions among peers and leadership, and remain open to feedback.
Skills
Software Development
Infrastructure
Data Applications
Agile Methodology
Platform Development
Tool Development
Resiliency
Scalability
High Availability
TetraScience
Cloud platform for scientific data management
About TetraScience
TetraScience offers a cloud-based platform called the Scientific Data Cloud, which helps biopharmaceutical companies manage and harmonize their scientific data for research and development, quality assurance, and manufacturing. The platform connects various lab instruments and software, streamlining data management and significantly reducing task completion time. TetraScience's vendor-neutral and open design allows it to work with any lab equipment, making it a flexible solution in the life sciences sector. The company's goal is to enhance scientific outcomes by preparing data for artificial intelligence and machine learning applications.
Boston, MassachusettsHeadquarters
2019Year Founded
$113.8MTotal Funding
SERIES_BCompany Stage
AI & Machine Learning, Biotechnology, HealthcareIndustries
51-200Employees
Benefits
Unlimited PTO
100% company paid health, dental, & vision
Company paid life insurance
401k savings
Company paid disability insurance
Equity program
Flexible work arrangements
Risks
Rapid AI development may outpace TetraScience's integration capabilities, risking obsolescence.
Dependency on partners like Google Cloud and NVIDIA could pose risks if disrupted.
International expansion may expose TetraScience to regulatory and compliance challenges.
Differentiation
TetraScience offers a vendor-neutral, open, cloud-native platform for scientific data management.
The platform integrates with any lab equipment or software, enhancing flexibility and adaptability.
TetraScience's Scientific Data Cloud centralizes and harmonizes data, preparing it for AI/ML applications.
Upsides
Partnerships with NVIDIA and Google Cloud enhance AI-native scientific datasets and capabilities.
Collaboration with Databricks accelerates the Scientific AI revolution in life sciences.
Bayer AG partnership maximizes scientific data value, driving innovation in biopharma.
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