Data Engineer

Key Skills

Python Programming, Azure, AWS, Apache Airflow, Docker, Kubernetes-K8s, Google Cloud Platform (GCP), Data pipelines, Programming, Luigi

Job Description

Chemix is seeking a highly-motivated data engineer to develop and expand our AI platform for battery materials discovery. Our AI platform is the core of Chemix. Though data is first and foremost in any application of AI, it is typically very scarce in materials development. We've designed our entire R&D operation to generate battery materials datasets of unprecedented size and quality. As a data engineer at Chemix, your mission is to build and extend the data pipelines that turn this data into actionable results. You'll make a fundamental contribution to developing the batteries that will power the electrification revolution in transportation and beyond.

As an early employee at a fast-moving startup, we expect you to quickly and creatively solve all kinds of technical problems, including those beyond your core expertise. An ideal candidate is able to learn quickly, is eager to stretch their knowledge of the data and ML software stack, takes pride in the quality of their work, and wants to make a real impact in energy storage technologies for electric transportation.

Responsibilities:

• Develop data pipelines for various types of battery data and use cases
• Introduce new data frameworks, workflows, and libraries, and best practices
• Contribute code to Chemix's internal codebase (Python)
• Interface with our machine learning engineers and battery engineers to enable them to access the data they need
• Inform the optimization of the R&D process that generates our data

Requirements

• Bachelor's degree in computer science, or the physical, chemical, or biological sciences, combined with 2+ years of work experience in data engineering
• Extensive experience with the python data stack: pandas, numpy, Dask
• Experience with workflow orchestration tools, e.g. Airflow, Prefect, Luigi
• Experience with data/software ops: git, testing, CI/CD, deployment
• Clear communication and good people skills
• Strong organization and ability to manage parallel projects

Nice to have:

• Experience with cloud web services (AWS, Google Cloud, Azure, etc.), Docker, Kubernetes
• Familiarity with experimental chemistry/materials science

Benefits

• Stock Option Plan
• Health Care Plan (Medical, Dental & Vision)
• Retirement Plan (401k)
• Paid Time Off (Vacation, Sick & Public Holidays)
• Family Leave (Maternity, Paternity)