Sr Big Data Engineer
hace 2 semanas
**About the Role**:
**What you will be doing**
- Build a reusable, and reliable code for stream and batch processing systems at scale. This includes working with technologies like Pub/Sub, Kafka, Kinesis, DataFlow, Flink, Hadoop, Pig, Hive, and Spark. Implementing automation/DevOps best practices for CI/CD, IaC, Containerization, etc.
**Requirements**:
- Experience in building a reusable, and reliable code for stream and batch processing systems at scale.
- 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.
- Ability to tackle complex challenges and devise effective solutions. Use critical thinking to approach problems from various angles and propose innovative solutions.
- 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
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