Data Reliability Engineer III - India

Requirements

• Education: Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related field.
• Experience: 5+ years of experience in data engineering or data science on GCP.
• Proven experience as a Data SRE or similar role focused on infrastructure management.
• Solid understanding of SRE practices and software development best practices (Git, CI/CD).
• Technical Proficiency:
• GCP Services: BigQuery, Dataflow, Data Fusion, Dataproc, Cloud Composer, Pub/Sub, and Google Cloud Storage.
• Programming: Strong skills in Python (NumPy, Pandas, PySpark), Java (Spark, functional interfaces), or Scala.
• Data Tools: Relational databases, data warehousing, big data platforms, and data streaming (e.g., Kafka).
• Monitoring: Experience with Cloud Logging, ELK Stack, AppDynamics, New Relic, or Splunk.
• Preferred Skills:
• Google Associate Cloud Engineer or Data Engineer certification.
• Experience with Docker and Kubernetes.
• Knowledge of AI and ML tools.
• CME Group: Where Futures are Made
• At CME Group, we embrace our employees' unique experiences and skills to ensure that everyone's perspectives are acknowledged and valued. As an equal-opportunity employer, we consider all potential employees without regard to any protected characteristic.

Additional Information

The core responsibilities focus on the reliability, automation, and performance of data systems on the Google Cloud Platform (GCP): Infrastructure & Automation: Design, build, secure, and maintain data infrastructure, including pipelines, warehouses, and processing platforms. This includes developing automation scripts to streamline operations and ensure scalability for growing data volumes. Monitoring & Incident Response: Implement robust monitoring and alerting systems to proactively identify issues. You must respond to incidents promptly to minimize downtime and data loss. Quality & Optimization: Measure and monitor data quality. Optimize systems to reduce latency, improve performance, and ensure efficient processing. Collaboration: Work with data scientists, domain owners, and infrastructure teams to ensure effective data consumption, forecast growth, and plan capacity. Security & Compliance: Ensure data security and compliance with protection regulations by implementing access controls and encryption. Documentation: Maintain clear, up-to-date documentation for systems, configurations, and standard operating procedures.

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