Data Engineer Spring Co-op_Spring 26

Found Energy•Boston, MA

48d

About The Position

Found Energy is at the cutting edge of hydrogen generation technology, pioneering systems that have the potential to revolutionize energy solutions worldwide. As we scale our reactor systems to support our minimum viable product (MVP) and commercial pilot demonstrations, we are building data infrastructure and analytics capabilities to support operational insights, optimization, and decision-making. As a Data Engineer Co-op, you will be instrumental in building and maintaining the data infrastructure necessary to analyze and improve our pilot systems. You will work closely with our R&D, automation, and engineering teams to collect, organize, and analyze data generated by our systems. You will also collaborate closely with our chemistry and materials science teams to support experiment tracking, characterization workflows, and data management for lab-based R&D. Your work will help drive efficiency, reliability, and scalability in our operations, playing a key role in advancing our mission to create impactful climate technologies. Co-op Duration: 6 months, with potential extension. January 2026- June 2026

Requirements

Passionate about climate tech and its potential to impact the world.
Pursuing a degree in Computer Science, Data Engineering, Software Engineering, Applied Math, or a related field.
Familiarity with programming languages such as Python and SQL
Experience with data processing frameworks such as Pandas, Apache Spark, or similar.
Knowledge of relational databases (e.g., PostgreSQL, MySQL)
Familiarity with cloud platforms (e.g., AWS, Azure, or Google Cloud) and their data engineering tools.
Understanding of data visualization tools (e.g., Tableau, Power BI, or Matplotlib).
Experience with version control systems like Git and collaborative workflows.
Ability to understand scientific data structures, such as experiment logs, sample metadata, or characterization results.
Ability to work in a multidisciplinary environment, collaborating with hardware, software, and chemical engineers.
Strong analytical, problem-solving, and communication skills.

Nice To Haves

Experience with time-series databases (e.g., InfluxDB, TimescaleDB).
Experience working in a scientific or research lab environment
Exposure to data generated from chemistry, materials science, or analytical instruments (e.g., ICP-MS, XRD, SEM, NMR, titrations).
Exposure to IoT devices and edge computing.
Familiarity with basic chemistry or lab workflows (e.g., wet lab experiments, sample preparation, or analytical instrumentation) is a plus.

Responsibilities

Design, build, and maintain scalable data pipelines to collect and process real-time and historical data from pilot systems and lab systems.
Support chemistry and materials science workflows by building tools for experiment tracking, sample management, and characterization data ingestion.
Develop and optimize database schemas and storage solutions for structured and unstructured data.
Integrate data from diverse sources, including sensors, control systems, and third-party APIs, ensuring data quality and consistency.
Collaborate with automation and R&D teams to define data requirements for system monitoring and performance analysis.
Create dashboards and visualizations to monitor system performance, enabling data-driven decision-making.
Develop and implement algorithms for data analysis, including trend detection, anomaly identification, and predictive modeling.
Ensure data security, integrity, and compliance with company and industry standards.
Participate in design reviews and contribute to the development of best practices for data engineering processes.
Document data workflows, pipelines, and technical procedures.