Byterat is the modern platform for battery science. We give battery teams at leading electric vehicle, grid storage, electronics and materials companies (e.g. Panasonic, Tesla) the core data platform they need to innovate, securely at scale.
We’re a well-funded, VC-backed start-up with customers and recurring revenue. We’re backed by world-class investors like Y Combinator, Giant Ventures and Collaborative Fund, and angels such as founders of Zendesk and Voi, and executives from Google, Meta and Figma.
The Byterat platform operates in battery labs across three continents and our reach is growing rapidly, which presents career-defining opportunities for ambitious engineers to accelerate their growth and contribute to a quickly evolving startup in SF. You’ll be joining our team of engineers and physicists with backgrounds from U. Cambridge, Georgia Tech, U. Waterloo and other YC start-ups.

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 forecast to spend $515B on electric vehicle and battery R&D by 2030. Yet battery engineers are underserved by software, relying on broken legacy products to analyze their data. Most data is never analyzed or used meaningfully.
Byterat provides battery teams with the data foundation needed to unlock business value from their battery data. Labs use Byterat to analyze data from thousands of parallel experiments and unlock previously hidden insights connecting battery design to performance.

You’ll take ownership for delivery and maintenance of a secure, scalable, cost-effective and reliable data pipeline and database that can support TBs data processed / year.
You’ll take ownership for technical integration of new customer data, including onboarding historical data, setting up continuous synchronization and guaranteeing security.
You’ll take ownership for management, operation and improvement of our associated cloud infrastructure.
You’ll work with our full-stack and back-end engineers to deliver advanced data engineering product features. This might include built-in modelling, custom metrics and anomaly flagging.
For the right candidate, this role has potential to evolve into a Head of Data Engineering leadership role.

You have previously built and delivered a reliable, scalable data pipeline for processing large amounts of data.
Extreme ownership mentality - you own problems end-to-end and you’ll leverage all your resources to get the job done.
You’re a team player. 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’re reliable on delivering on technical milestones.
You’re intrinsically motivated and set an exceptionally high performance bar for yourself.
You communicate effectively and respectfully. You pay attention to details. You express ideas clearly, you listen with openness. You have the confidence to communicate what is working and what needs to change.

Must-have

BS or MS in Computer Science, Engineering, or a related field.
You have experience owning the production, operations and reliability of a data pipeline.
You have 3+ years experience in ETL processes, data modeling, and data engineering best practices.
You have experience with streaming technologies (e.g. Spark, Flink, Google Pub/Sub, Kafka, Amazon Kinesis)
You have experience with NoSQL and distributed database technologies (e.g. Cassandra, HBase, DynamoDB, BigTable, ClickHouse)
You are well-versed with cloud environments such as AWS, Azure, and GCP, associated cloud storage technologies (S3, GCS) and Kubernetes-based orchestration.
Familiarity with time series data and tools such as PostgreSQL, Druid, TimescaleDB, and InfluxDB.

Nice-to-have

Experience with our tech stack: Postgres database with data indexing using ElasticSearch, modern Python-based ETL with a NodeJS / NextJS GraphQL layer, React TypeScript front-end, hosted in AWS with Kubernetes
Monitoring & Scripting: Expertise in monitoring tools (Prometheus, OpenTelemetry, ELK Stack) and strong scripting skills in Bash or Python.
Machine Learning: Understanding of integrating machine learning models into data workflows to extract meaningful insights.

Byterat

Lead Data Engineer