Senior R&D Data Engineer

About the role

Lydian is creating sustainable aviation fuels by converting waste CO2, water, and renewable electricity into low-emission alternatives. We are seeking a senior data professional to construct and manage the technical data infrastructure as we transition from pilot-scale operations to commercial production.

Key facts

What you'll do

• Architect and manage data storage systems across platforms like Nominal and Notion to ensure experimental, manufacturing, and quality data are organized and searchable.
• Develop custom visualization tools and automated dashboards to streamline performance metric tracking for our engineering and science teams.
• Configure and maintain data acquisition software such as DAQ Factory or Ignition to ensure reliable streaming from lab equipment.
• Execute statistical and regression analyses to identify correlations between manufacturing processes and experimental outcomes.
• Collaborate with mechanical and process engineers to refine data workflows and manage internal server and software infrastructure.

Requirements

• BS or MS degree in engineering, physical science, computer science, or data science.
• Minimum of 5 years of professional experience managing data within a hardware, laboratory, or physical science R&D setting.
• Advanced proficiency in SQL and Python, including schema design, query optimization, and usage of pandas and NumPy.
• Direct experience processing time-series and sensor data, including managing schema drift and data alignment.
• Expertise in at least one data acquisition platform such as LabVIEW, DAQ Factory, or Ignition.
• Ability to perform statistical analysis and translate findings into clear visual reports.
• Experience using AI coding assistants for pipeline development and debugging with a focus on output validation.

Nice to have

• Academic or professional background in chemical, materials, or mechanical engineering.
• Familiarity with modern data stack tools including Airflow, Dagster, dbt, Snowflake, DuckDB, or Iceberg.
• Experience with automated testing frameworks like Great Expectations.
• Prior use of JMP, Notion, or Nominal.
• Fundamental IT and networking skills.

Skills & tools

• Python, SQL, pandas, NumPy
• DAQ Factory, Ignition, LabVIEW
• Nominal, Notion
• Statistical and regression analysis
• Data pipeline architecture

Practical notes

• Benefits include 100% coverage of medical, vision, and dental premiums for employees and 80% for dependents.
• The package includes a 401(k) plan with company match and flexible PTO.