Infrastructure Engineer

Job Title: DevOps Engineer / Infrastructure Engineer
Location: Cupertino, CA / Seattle, WA (Hybrid - 3 days onsite)
Duration: 12-month contract (Initial)

Job Description

Summary

The Data Infrastructure group within the AI/ML organization powers the analytics, experimentation and ML feature engineering that powers the Machine Learning technologies we all love in our Our mission is to provide cutting edge, reliable and easy to use infrastructure for ingesting, storing, processing and interacting with data while keeping users' data private and

The Data Security and Privacy team sits within the AI/ML Data Infrastructure group and is looking for engineers who want to bring their passion for security and privacy to help build world class data infrastructure that puts users' privacy first while enabling data engineers and scientists to produce world-beating ML data

Key Qualifications

• 3+ years of experience scaling and operating distributed systems like big data processing engines (, Apache Hadoop, Apache Spark), distributed file systems ( HDFS, CEPH, S3, ), streaming systems (, Apache Flink, Apache Kafka), resource management systems (, Apache Mesos, Kubernetes), or Identity and Access Management ( Apache Ranger, Sentry, OPA)
• 3+ years experience with infrastructure as code and systems automation
• Fluency in Java or a similar language
• Ability 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 Spark and ETL processing pipelines is helpful, but not required
• Experience with systems security, identity protocols and encryption is helpful, but not required

Description

The ideal candidate will have outstanding communication skills, proven data infrastructure design and implementation capabilities, strong business acumen, and an innate drive to deliver They will be a self-starter, comfortable with ambiguity and will enjoy working in a fast-paced dynamic

Responsibilities include:

• Scale and operationalize privacy and security systems in a big data environment leveraging technologies like Spark, Kafka, Presto, Flink, Hadoop in both on-premise and AWS environment through automation and infrastructure-as-code
• Ensure data infrastructure offers reliable high-quality data with consistent SLAs with good monitoring, alerting and incident response and continual investment to reduce tech-debt
• Write code, documentation, participate in code reviews and design sessions

Skills :