Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.
As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.
We operate development centers in Plymouth, Michigan; Southern California (Irvine, Carson & LA); Silicon Valley (San Jose and Palo Alto); Vancouver, British Columbia; and Surrey, England; as well as a manufacturing facility in Normal, Illinois.
The Information Technology org at Rivian is seeking a Staff, Data DevOps Engineer to join the Data Engineering team.
You will work with other engineers and technical resources from cross-functional teams to build a fully automated Data and Machine Learning infrastructure and set the diverse components of a scalable data platform that will serve business stake holders across Rivian
- Build Data and Machine Learning infrastructure using infra-as-code on AWS. Set-up automated workflows to securely and seamlessly onboard data scientists and data engineers to build and consume end-to-end data and ML pipelines
- Set-up and configure the components of a scalable data platform, namely AWS EMR, Kafka, AWS Sagemaker, Apache Spark, AWS Redshift, Snowflake, AWS Glue, Kubernetes/K8s, Athena, Apache Kylin etc.
- Manage and maintain the Source Code Repository (SCM) systems like Gitlab, BitBucket
- Create release automation/CICD pipelines to securely build, package and deploy code and machine learning model artifacts
- Define and deploy a logging, monitoring and alerting infrastructure using Splunk, Prometheus/ DataDog, AWS CloudWatch, PagerDuty
- Define and enforce security best practices on the data plane Vs control plane and manage tagging and metering across multiple AWS accounts in a multi-tenant data platform
- Set-up and manage internal and external API Gateways, load balancers and container orchestration on Kubernetes
- Manage release management of database assets (SQL scripts/ schemas) using tools like LiquidBase, Switch or Flyway
- Automate security gates to enable rapid and iterative development activities
- Build data science and machine learning orchestration and automate data exploration, experiments, model building, training and deployments, model monitoring and re-training
- Overall 8-12+ years of software development experience, including 4+ years of dedicated DevOps experience building Infrastructure as code using CloudFormation, Terraform
- Experience with entire DevOps lifecycle - Orchestration, Configuration, CI/CD, Monitoring, Security
- 3-4 years working specifically on the data domain ecosystems namely setting up and managing data lakes in S3, SQL data warehouses like Redshift, Snowflake and a set of federated databases like AWS Dynamo, AWS Aurora, Elastic Cache, Hbase
- 2+ years running a data science/machine learning ecosystem on AWS Sagemaker or Databricks. Strong knowledge of ML Orchestration such as AWS SageMaker, Kubeflow, Databricks MLFlow is highly desired
- Experience with laying down best practices for managing multiple AWS accounts and separating the data plane from the control plane
- Experience with the Kubernetes container orchestration, service data mesh and service discovery frameworks
- Experience with multi-tier architectures: API Gateways, load balancers, networking fundamentals
- Certified on at least one: AWS DevOps Engineering, AWS Certified Developer - Associate, or AWS Certified SysOps Administrator - Associate, Kubernetes K8 certification
Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law.
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