Scientific Data Engineer

Responsibilities

• Onboarding of approximately 50 laboratory instruments onto the TetraScience Data Platform:
  • Development of instrument parsers as required
  • Design and development of data pipelines to support data flow and accessibility
  • Provide solution guidance to the Systems Integrations team on Integration solution guidance between TetraScience and Revvity ELN
• Activities Performed:
  • User Story creation & refinement
  • Raw-to-IDS, metadata attribution
  • instrument onboarding
  • parser development, testing, etc.
• Note that this does not include integrations of system with ELN, NNCD, Inventory management, etc

What we expect

• Expertise working with data from laboratory equipment/software, (e.g. LIMS, ELN, etc.)
• Bachelor’s degree in Engineering, Data Science, Life Sciences, Computer Science, or related field; advanced degree preferred.
• 5+ years of experience in data engineering, including data modeling and database design, preferably in a scientific, manufacturing, or healthcare environment.
• Proficiency with Python, R, SQL, and cloud-based architectures (AWS services, Snowflake, Databricks, Redshift).
• Expertise in ETL and DWH.
• Experience with NoSQL and graph databases.
• English language proficiency of B2+
• Strong analytical, problem‑solving, and stakeholder‑management skills, with the ability to translate discussions into actionable requirements.
• Experience in Data Platform integrations, preferably in Life Sciences/biotech domain

Nice to have

• Proficiency with Revvity's Signals ELN
• Expertise in TetraScience Data Platform

We offer

• Competitive compensation
• Remote or office work
• Flexible working hours
• Continuous education, mentoring, and professional development programs
• A team with an excellent tech expertise
• Certifications paid by the company