Description
Data System Reliability Engineer (dSRE)
Role Overview:
A crucial role in CME's Cloud data transformation, the data SRE will be aligned to data product pods ensuring the our data infrastructure is reliable, scalable, and efficient as the GCP data footprint expands rapidly.
Accountabilities:
Automate data tasks on 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: Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science or related field, or equivalent practical experience
Experience as a Data Site Reliability Engineer or a similar role, with a focus on data infrastructure management
Proficiency in data technologies, such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., Kafka), and cloud services (e.g., AWS, GCP, Azure).
Ideally some programming skills in languages like Python, Java, or Scala, with experience in automation and scripting.
Experience with containerization and orchestration tools like Docker and Kubernetes is a plus.
Experience with data governance, data security, and compliance best practices.
Understanding of software development methodologies and best practices, including version control (e.g., Git) and CI/CD pipelines.
Analytical and problem-solving abilities, with a proactive attitude towards identifying and resolving issues.
Excellent communication and collaboration skills to work effectively in a team-oriented environment.
Ideally a background in cloud computing and data-Intensive applications and services, with a focus on Google Cloud Platform
3+ years of experience in data engineering or data science.
Experience with data quality assurance and testing.
Ideally knowledge of GCP data services (BigQuery; Dataflow; Data Fusion; Dataproc; Cloud Composer; Pub/Sub; Google Cloud Storage)
Understanding of logging and monitoring using tools such as Cloud Logging, ELK Stack, AppDynamics, New Relic, Splunk, etc.
Proven ability to learn new technologies, including open source and cloud-native offerings
Knowledge of AI and ML tools is a plus
Google Associate Cloud Engineer or Data Engineer certification is a plus
Responsibilities: Automate provisioning of infrastructure as code, using tools such as Terraform and KCC
Build self-service capabilities for development teams to improve time-to-market and promote cloud adoption
Create CI/CD pipelines using Jenkins, Bitbucket/Git
Create monitoring dashboards and metrics using Splunk, Prometheus, Grafana
Write unit tests in Go/Python/Java
Work on a globally distributed team
CME Group: Where Futures Are Made
CME Group (www.cmegroup.com) is the world's leading derivatives marketplace. But who we are goes deeper than that. Here, you can impact markets worldwide. Transform industries. And build a career shaping tomorrow. We invest in your success and you own it, all while working alongside a team of leading experts who inspire you in ways big and small. Problem solvers, difference makers, trailblazers. Those are our people. And we're looking for more.
At CME Group, we embrace our employees' diverse experiences, cultures and skills, and work to ensure that everyone's perspectives are acknowledged and valued. As an equal opportunity employer, we recognize the importance of a diverse and inclusive workplace and consider all potential employees without regard to any protected characteristic. The Candidate Privacy Policy can be found here.
#J-18808-Ljbffr
Role Overview:
A crucial role in CME's Cloud data transformation, the data SRE will be aligned to data product pods ensuring the our data infrastructure is reliable, scalable, and efficient as the GCP data footprint expands rapidly.
Accountabilities:
Automate data tasks on 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: Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science or related field, or equivalent practical experience
Experience as a Data Site Reliability Engineer or a similar role, with a focus on data infrastructure management
Proficiency in data technologies, such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., Kafka), and cloud services (e.g., AWS, GCP, Azure).
Ideally some programming skills in languages like Python, Java, or Scala, with experience in automation and scripting.
Experience with containerization and orchestration tools like Docker and Kubernetes is a plus.
Experience with data governance, data security, and compliance best practices.
Understanding of software development methodologies and best practices, including version control (e.g., Git) and CI/CD pipelines.
Analytical and problem-solving abilities, with a proactive attitude towards identifying and resolving issues.
Excellent communication and collaboration skills to work effectively in a team-oriented environment.
Ideally a background in cloud computing and data-Intensive applications and services, with a focus on Google Cloud Platform
3+ years of experience in data engineering or data science.
Experience with data quality assurance and testing.
Ideally knowledge of GCP data services (BigQuery; Dataflow; Data Fusion; Dataproc; Cloud Composer; Pub/Sub; Google Cloud Storage)
Understanding of logging and monitoring using tools such as Cloud Logging, ELK Stack, AppDynamics, New Relic, Splunk, etc.
Proven ability to learn new technologies, including open source and cloud-native offerings
Knowledge of AI and ML tools is a plus
Google Associate Cloud Engineer or Data Engineer certification is a plus
Responsibilities: Automate provisioning of infrastructure as code, using tools such as Terraform and KCC
Build self-service capabilities for development teams to improve time-to-market and promote cloud adoption
Create CI/CD pipelines using Jenkins, Bitbucket/Git
Create monitoring dashboards and metrics using Splunk, Prometheus, Grafana
Write unit tests in Go/Python/Java
Work on a globally distributed team
CME Group: Where Futures Are Made
CME Group (www.cmegroup.com) is the world's leading derivatives marketplace. But who we are goes deeper than that. Here, you can impact markets worldwide. Transform industries. And build a career shaping tomorrow. We invest in your success and you own it, all while working alongside a team of leading experts who inspire you in ways big and small. Problem solvers, difference makers, trailblazers. Those are our people. And we're looking for more.
At CME Group, we embrace our employees' diverse experiences, cultures and skills, and work to ensure that everyone's perspectives are acknowledged and valued. As an equal opportunity employer, we recognize the importance of a diverse and inclusive workplace and consider all potential employees without regard to any protected characteristic. The Candidate Privacy Policy can be found here.
#J-18808-Ljbffr
