Data Reliability Engineer II

As the world’s leading and most diverse derivatives marketplace, CME Group (www.cmegroup…

Accountabilities

• Automate data tasks on Google Cloud Platform (GCP).
• Work with data domain owners, data scientists, and other stakeholders to ensure that data is consumed effectively on GCP.
• Design, build, secure, and maintain data infrastructure, including data pipelines, databases, data warehouses, and data processing platforms on GCP.
• Measure and monitor the quality of data on GCP data platforms.
• Implement robust monitoring and alerting systems to proactively identify and resolve issues in data systems.
• Respond to incidents promptly to minimize downtime and data loss.
• Develop automation scripts and tools to streamline data operations and make them scalable to accommodate growing data volumes and user traffic.
• Optimize data systems to ensure efficient data processing, reduce latency, and improve overall system performance.
• Collaborate with data and infrastructure teams to forecast data growth and plan for future capacity requirements.
• Ensure data security and compliance with data protection regulations.
• Implement best practices for data access controls and encryption.
• Collaborate with data engineers, data scientists, and software engineers to understand data requirements, troubleshoot issues, and support data-driven initiatives.
• Continuously assess and improve data infrastructure and data processes to enhance reliability, efficiency, and performance.
• Maintain clear and up-to-date documentation related to data systems, configurations, and standard operating procedures.

Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or a related field, or equivalent practical experience.
• Professional Experience: Experience as a Site Reliability Engineer or a similar role with a strong focus on data infrastructure management.
• Methodologies: Understanding of Site Reliability Engineering (SRE) practices.
• Data Technologies: Proficiency in data technologies such as relational databases, data warehousing, big data platforms (e.g., Hadoop), data streaming (e.g., Kafka), and cloud services (e.g., AWS, GCP, Azure).
• Programming Skills: Programming skills in languages like Python (NumPy, pandas, PySpark), Java (Core Spark with Java, functional interface, collections), or Scala with experience in automation and scripting.
• Infrastructure Tools: Experience with containerization and orchestration tools like Docker and Kubernetes is a plus.
• Compliance: Experience with data governance, data security, and compliance best practices on GCP.
• Software Development: Understanding of software development methodologies and best practices, including version control (e.g., Git) and CI/CD pipelines.
• Cloud Computing: Any experience in cloud computing and data-intensive applications and services, ideally Google Cloud Platform (GCP) would be highly beneficial.
• Quality Assurance: Experience with data quality assurance and testing on GCP.
• GCP Data Services: Proficiency with GCP data services (BigQuery, Dataflow, Data Fusion, Dataproc, Cloud Composer, Pub/Sub, Google Cloud Storage).
• Monitoring Tools: Understanding of logging and monitoring using tools such as Cloud Logging, ELK Stack, AppDynamics, New Relic, and Splunk.
• Advanced Tech: Knowledge of AI and ML tools is a plus.
• Certifications: Google Associate Cloud Engineer or Data Engineer certification is a plus.

Company Benefits

• Bonus Programme
• Equity Programme
• Employee Stock Purchase Plan (ESPP)
• Private Medical and Dental coverage
• Income Protection
• Life Assurance
• Cycle To Work
• Family Leave
• Education Assistance – MBA/Advanced Degree/Bachelor Degree
• Ongoing Employee Development Training/Certification

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