Data Infrastructure Engineer

Data Infrastructure Engineer

W2 Contract

Salary Range: $135,200 -$156,000 per year

Location: Cupertino, CA - Remote Role

Job Summary:

The mission of the Data Infrastructure org is to provide cutting-edge, reliable, and easy-to-use infrastructure for ingesting, storing, processing, and interacting with data and help the teams that build data-intensive applications be successful.

We are looking for engineers who want to bring their passion for infrastructure to build world-class products. You will develop and lead our data infrastructure team and help your team members grow technically and professionally. You will work with many cross-functional teams and lead the planning, execution, and success of technical projects to improve the service experience for our customers.

The ideal candidate will have outstanding communication skills, proven data infrastructure design and implementation capabilities, strong business acumen, and an innate drive to deliver results.

Duties and Responsibilities:

• Build and operate our data infrastructure supporting millions of users at 100+ PB scale.


• Scale and operationalize big data technologies like Spark, Kafka, Presto, Flink, and Hadoop in both on-premise and AWS environments.


• Ensure data infrastructure offers reliable, high-quality data with consistent SLAs, sound monitoring, alerting, incident response, and continual investment to reduce tech debt.


• Write code and documentation, participate in code reviews, and mentor other engineers.

Requirements and Qualifications:

• B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or equivalent practical experience


• Experience managing Kubernetes clusters and running distributed applications in a Kubernetes environment.


• Familiar with AWS technologies such as EC2, S3, RDS, and IAM.


• Fluency in Python, Java, or scripting language.


• Able to debug complex issues in large-scale distributed systems


• Passion for building infrastructure that is reliable, easy to use, and easy to maintain


• Excellent communication and collaboration skills


• Experience with distributed systems such as Spark, Flink, Kafka, and Cassandra is helpful but not required.

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