Sr Big Data Infrastructure Engineer (GCP)
United States - Remote
Applications have closed
Rackspace
As a cloud computing services pioneer, we deliver proven multicloud solutions across your apps, data, and security. Maximize the benefits of modern cloud.What you will be doing:
- Implementing automation/DevOps best practices for CI/CD, IaC, Containerization, etc to Build a reusable infra structure for stream and batch processing systems at scale.
- Create automation, whether that is building DevOps pipelines, scripting or creating Infrastructure as Code in Terraform
- Participating in work sessions with clients
- Completing technical documentation
Requirements:
- Experience in Developing and Scaling data Processing Systems This includes working with technologies like Pub/Sub, Kafka, Kinesis, DataFlow, Flink, Hadoop, Pig, Hive, and Spark.
- Expertise in public cloud services, particularly in GCP.
- Experience with GCP managed services and understanding of cloud-based messaging/stream processing systems are critical.
- Experienced in Infrastructure and Applied DevOps principles in daily work. Utilize tools for continuous integration and continuous deployment (CI/CD), and Infrastructure as Code (IaC) like Terraform to automate and improve development and release processes.
- Has knowledge in containerization technologies such as Docker and Kubernetes to enhance the scalability and efficiency of applications.
- Worked effectively in a remote setting, maintaining strong written and verbal communication skills. Collaborate with team members and stakeholders, ensuring clear understanding of technical requirements and project goals.
- Proven experience in engineering stream/batch processing systems at scale.
- Strong programming abilities in Java and Python.
- Hands-on experience in public cloud platforms, particularly GCP. Additional experience with other cloud technologies is advantageous.
Must Have:
- Google Associate Cloud Engineer Certification or other Google Cloud Professional level certification
- 4+ years of experience in customer-facing software/technology or consulting
- 4+ years of experience with “on-premises to cloud” migrations or IT transformations
- 4+ years of experience building, and operating solutions built on GCP (ideally) or AWS/Azure
- Technical degree: Computer Science, software engineering or related
About Rackspace TechnologyWe are the multicloud solutions experts. We combine our expertise with the world’s leading technologies — across applications, data and security — to deliver end-to-end solutions. We have a proven record of advising customers based on their business challenges, designing solutions that scale, building and managing those solutions, and optimizing returns into the future. Named a best place to work, year after year according to Fortune, Forbes and Glassdoor, we attract and develop world-class talent. Join us on our mission to embrace technology, empower customers and deliver the future. More on Rackspace TechnologyThough we’re all different, Rackers thrive through our connection to a central goal: to be a valued member of a winning team on an inspiring mission. We bring our whole selves to work every day. And we embrace the notion that unique perspectives fuel innovation and enable us to best serve our customers and communities around the globe. We welcome you to apply today and want you to know that we are committed to offering equal employment opportunity without regard to age, color, disability, gender reassignment or identity or expression, genetic information, marital or civil partner status, pregnancy or maternity status, military or veteran status, nationality, ethnic or national origin, race, religion or belief, sexual orientation, or any legally protected characteristic. If you have a disability or special need that requires accommodation, please let us know.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Azure Big Data CI/CD Computer Science Consulting Dataflow DevOps Docker Engineering Flink GCP Google Cloud Hadoop Java Kafka Kinesis Kubernetes Pipelines Python Security Spark Terraform
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