Tech Lead, Data Engineering

Tech Lead, Scientific Data Engineering

Engineering | Full-Time

Location: Hybrid, Cambridge, MA

About the Company

Our client is a Scientific Data and AI company with a mission to radically improve and extend human life. It combines an open, purpose-built scientific data and AI cloud with deep scientific expertise to turn lab data into AI-native datasets, powering a growing suite of lab data management products, scientific use cases, and AI-based outcomes.

Opportunity

Lead a team of Scientific Data Engineers building the data engineering foundation behind the company’s products. This role suits an experienced, hands-on data engineering leader who also mentors junior engineers. You will manage engineering tasks, lead design sessions, implement solutions, and drive projects to production release. You will work directly with Product Managers, Scientific Business Analysts, and Solution Architects to turn business and data design objectives into mission-critical customer implementations.

Key Responsibilities

• Own project delivery: lead a team of Scientific Data Engineers and supervise their career growth and performance.
• Work with cross-functional teams to understand business requirements, recommend outcomes, and build solutions based on consensus.
• Own the data models, data pipelines, and data applications that drive customer success.
• Use LLMs to build data schemas and parsers for pre-clinical data from R&D lab instruments, manufacturing, CROs, CDMOs, ELNs, and LIMS, across formats such as .xlsx, .pdf, .txt, .raw, .fid, and other vendor binaries.
• Extract reusable schema components and parsing functions and productize them into Python libraries.
• Build high-quality data pipelines with full unit and integration test coverage to produce high-fidelity data.
• Build data applications, reports, and dashboards using React, Streamlit, Jupyter, and similar tools.
• Verify that solutions meet customer requirements and deliver value.
• Act as quality gatekeeper, and promote team-wide improvements to product quality and developer experience.
• Rally the team to meet Agile sprint commitments, surface inefficiencies, and resolve blockers quickly.

Basic Qualifications

• 10+ years building solutions as a Data Engineer or in a similar field.
• 10+ years working in Python and SQL with a focus on data.
• Experience leading projects, managing requirements, and handling timelines.
• Experience managing multiple customer-focused projects across cross-functional teams, building sustainable processes, and managing delivery milestones.
• Experience driving engineering excellence by uncovering and resolving delivery challenges and inefficiencies.
• Excellent communication skills, attention to detail, and the confidence to take control of project delivery.
• Ability to quickly understand a highly technical product and communicate effectively with product management and engineering.