Tech Lead, Scientific Data Engineer - Remote

Overview

TetraScience is the Scientific Data and AI Cloud company with a mission to radically improve and extend human life. TetraScience combines the world's only open, purpose-built, and collaborative scientific data and AI cloud with deep scientific expertise across the value chain to accelerate and improve scientific outcomes. TetraScience is catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets, which it brings to life in a growing suite of next generation lab data management products, scientific use cases, and AI-based outcomes.

In Short

• Lead the Scientific Data Engineering Team and build Tetra Data.
• Act as a player-coach, providing mentorship to junior team members.
• Lead internal design sessions and architect solutions.
• Collaborate with Product Managers and Solution Architects on business and data design objectives.
• Build data models, prototypes, and integration solutions.
• Research data acquisition strategies for scientific lab instrumentation.
• Design with quality backed by unit tests and integration tests.
• Lead project post-mortems for continuous improvement.
• Facilitate Agile Sprint commitments and resolve team inefficiencies.
• Drive results by resolving blockers and making things happen.

Requirements

• Experience in data engineering and leading teams.
• Strong analytical and problem-solving skills.
• Proficiency in data modeling and integration.
• Familiarity with Agile methodologies.
• Excellent communication and collaboration skills.
• Ability to mentor and guide junior engineers.
• Experience with scientific data and AI technologies.
• Commitment to quality and customer success.
• Proactive approach to challenges and uncertainties.
• Strong organizational skills and attention to detail.

Benefits

• Collaborative and supportive work environment.
• Opportunity to lead impactful projects.
• Professional development and mentorship.
• Flexible work arrangements.
• Competitive salary and benefits package.
• Engagement in cutting-edge scientific data solutions.
• Commitment to diversity and equality of opportunity.
• Access to advanced technologies and tools.
• Chance to contribute to meaningful scientific outcomes.
• Supportive leadership that values transparency and collaboration.