Senior Data Engineer / Software Engineer (Telematics Insurance)
|Job Category||Engineering & Information Technology|
|Location||Palo Alto, California|
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Data is deeply embedded in the product and engineering culture at Tesla. We rely on data – lots of it – to improve autopilot, to optimize hardware designs, to proactively detect faults, and to optimize load on the electrical grid. We collect data from each of our cars, superchargers, and energy products and use it to make these products better and our customers safer.
We're the Fleet Analytics team, a small but fast-growing central team that helps many teams leverage the data we collect. We help engineers through direct support by doing data analysis for them and through applications and tools so they can self-serve those analyses in the future. To do so, we leverage the internal big data platform that is built on top of Kafka, Spark, Presto and data science tools such as Jupyter notebooks, Pandas, Bokeh, Superset and Airflow.
We're looking for an experienced data engineer to join us. This foundational member will provide leadership in the definition and implementation of processes and tools that enable Tesla's data science.
You will lead data collection work streams and build the machine learning data pipeline for our Telematics Insurance products, where customers pay a premium based on their driving behavior. You will collaborate with team across the stack, from firmware engineers to understand how and what to collect from the car, to data scientists to understand how to support their experiments and bring their models to production. By supporting these new insurance products, you will directly further our mission by making it more affordable to own a Tesla, as well as giving our customers feedback on how they can be safer drivers.
- Think through how to collect relevant data from cars, while protecting our customer's privacy
- Work across engineering teams to understand what data is available
- Be creative in identifying new driving behavior metrics that can help predict insurance losses
- Work with firmware engineers to collect even more accurate and descriptive data
- Build efficient and reproducible data pipelines processing petabytes of time series data using cutting-edge open source technologies
- Design data pipelines capable of supporting experimentation and rapid model iteration, simple deployment to production, and maintainability
- Work with the data science team to develop predictive features for use in their machine learning models
- Bring machine learning models to production, delivering consistent and timely information to our customers and to the insurance billing application
- Give talks, contribute to open source projects, and advance data science on a global scale
- Identify trends, invent new ways of looking at data, and get creative in order to drive improvements in both existing and future products
- Keep up to date on relevant technologies and frameworks, and propose new ones that the team could leverage
- Write clean and tested code that can be maintained and extended by other software engineers
- Present your results to Tesla's executive leadership
- Design and build the machine learning data pipeline
- Smart but humble, with a bias for action
- Experience running (machine learning) data pipelines
- Experience with data science tools such as Pandas, Numpy, R, Matlab, Octave
- Strong problem-solving skills to come up with good solutions to problems you are the first to tackle
- Strong verbal and written communication skills
- Strong foundation in software engineering
- Strong proficiency in Python
- Strong foundation in statistics
- Experience in the insurance industry
- Experience building web applications
- Experience building data visualizations
- Experience with continuous integration and continuous development
- Experience in devops, i.e. Linux, Ansible, Docker, Kubernetes
- Understanding of distributed computing, i.e. how HDFS, Spark and Presto work
- Proficient in Scala
Tesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws.