[Remote] Senior Scientific Data Engineer at TetraScience

United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Scientific Data, AI, Life SciencesIndustries

Requirements

8+ years of building solutions as a Data Engineer or similar fields
8+ years working in Python and SQL with a focus on data
6+ years of experience leading projects, managing requirements, and handling them

Responsibilities

Work with Product Managers and Solution Architects to understand business requirements, gather insight into potential positive outcomes, recommend potential outcomes, and build a solution based on consensus
Take ownership of building data models, prototypes, and integration solutions that drive customer success
Research and prototype data integration strategy for scientific lab instrumentation, prototype file parsers for instrument output files (.xlsx, .pdf, .txt, .raw, .fid, and many other vendor binaries)
Quality gatekeeper: design with quality backed by unit tests, integration tests, and utility functions
Lead team-wide process/technology improvements on product quality and developer experience
Rally the team to finish Agile Sprint commitments. Actively surfacing team inefficiencies and striving to resolve them
Driven by results. Have the pragmatic urgency to resolve blockers, unclear requirements, and make things happen
Provide mentorship to junior SDEs and show leadership in every front
Lead internal design sessions and architect solutions
Supervise and collaborate on project executions with a high commitment to customer success by delivering mission-critical implementations

Skills

Key technologies and capabilities for this role

Data EngineeringScientific DataAICloudETLData PipelinesPythonSQL

Questions & Answers

Common questions about this position

Is this position remote?

Yes, the position is remote.

What are the core values at TetraScience?

TetraScience's core values are Transparency and Context, Trust and Collaboration, Fearlessness and Resilience, Alignment with Customers, Commitment to Craft, and Equality of Opportunity.

What skills and experience are required for the Senior Scientific Data Engineer role?

The role requires being a player-coach data engineer who is experienced and hands-on, comfortable leading design sessions and architecting solutions, with excellent data engineering skills, ability to supervise and collaborate on projects, and a high commitment to customer success.

What is the salary or compensation for this role?

This information is not specified in the job description.

What makes a strong candidate for this position?

Strong candidates are high-performance team members who authentically embrace TetraScience's core values, have hands-on data engineering experience as a player-coach, can lead design sessions, architect solutions, mentor juniors, and are committed to collaboration and customer success.

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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