Excellent opportunity to join a well-funded, VC backed startup with customers and recurring revenue, as their Head of Engineering. The core product is a modern platform for battery science that battery teams can use to innovate, securely at scale. Labs use this platform to analyze data from thousands of parallel experiments and unlock previously hidden insights connecting battery design to performance. This platform operates in battery labs across three continents and their reach is growing rapidly.

This is the first platform of its kind to provide battery teams with the data foundation needed to unlock business value from their battery data. The addressable market is huge! Batteries play a key role in tackling climate change. $73B was invested in US battery plants in 2022, and battery company revenue is expected to grow >5x in the next decade. Car manufacturers alone are forecasting to spend $515B on electric vehicle and battery R&D by 2030. But battery engineers are underserved by software, relying on broken legacy products to analyze their data. Most data are never analyzed or used meaningfully.

The Head of Engineering role offers a career-defining opportunity for ambitious data engineers to accelerate their growth and contribute to a quickly evolving startup in the Silicon Valley. You’ll be joining an in-person team of engineers and physicists with backgrounds from U. Cambridge, Georgia Tech, U. Waterloo and other YC start-ups. This position offers strong equity (diluted), competitive compensation, excellent benefits, career development opportunities, and outstanding work environment.

In this role, you’ll:

Take ownership for overall technical execution of product roadmap, working closely with the CEO and CCO.

Take ownership for the security, performance, scalability and reliability of the data pipelines and web app.

Take responsibility for data architecture and engineering decisions, bringing your strong experience and knowledge to bear.

Build, test and ship software to manage, operate and improve the data pipelines and associated cloud infrastructure.

Take ownership for success of technical integrations.

This role will be a good fit for you if:

You have an entrepreneurial mindset. You are ambitious and you want to move fast. You want to accelerate your trajectory and have an outsized impact on a rapidly growing VC-backed startup.

You can lead the engineering team to peak performance but also enjoy hands-on technical work as you build out the team.

You own problems end-to-end, and you are willing to pick up whatever knowledge you're missing to get the job done.

You pay attention to details. You express ideas clearly; you listen with curiosity. You are not afraid to communicate what is working and what needs to improve.

You set an exceptionally high-performance bar for yourself and everyone on the team.

You are a team player and enjoy collaborating and brainstorming. You have a humble attitude, you take actions to help your colleagues, and you want to do whatever it takes to make the team succeed. You communicate effectively and respectfully.

Technical qualifications

This is a comprehensive and versatile position within the data engineering field. The ideal candidate is one with experience in roles that have incorporated modern data engineering and data pipelining tasks with elements of DevOps and/or SRE, Machine Learning, and full-stack development.

Must-have

BS or MS in Computer Science, Engineering, or a related field.

Experience in ETL processes, data modelling, and data engineering best practices (PySpark/ AWS EMR experience preferred)

DevOps and/or SRE experience beneficial for automating and optimizing data workflows You are well-versed with cloud platforms (AWS, Azure, GCP), CI/CD tools (GitLab CI, GitHub Actions, CircleCI), and infrastructure as code (Helm, Terraform, CloudFormation).

Time Series Data: Familiarity with time series data and tools such as PostgreSQL, Druid, Timescale DB, and Influx DB.

Containerization & Orchestration : Hands-on experience with Docker, Kubernetes, AWS EKS, and/or AWS Fargate for deploying and managing scalable data solutions.

Team execution: You have experience translating product requirements into clear technical milestones and delegating responsibilities appropriately across the engineering team. You have a track record of leading an engineering team to reliably deliver the product requirements on-time.

Nice-to-have

Monitoring & Scripting : Expertise in monitoring tools (Prometheus, Open Telemetry, ELK Stack) and strong scripting skills in Bash or Python essential for maintaining and automating data workflows, ensuring system reliability and troubleshooting issues.

Machine Learning: Understanding of integrating machine learning models into data workflows to extract meaningful insights and adding advanced scalability to data engineering tasks.

Experience with our client’s tech stack:

Postgres database with data indexing using Elasticsearch for efficient data retrieval and search capabilities

Modern python based ETL with a node.js / next.js GraphQL layer for building scalable and efficient data pipelines

React TypeScript front-end

Hosted in AWS with Kubernetes