Capgemini is a global leader in consulting, technology services and digital transformation, is at the forefront of innovation to address the entire breadth of clients opportunities in the evolving world of cloud, digital and platforms. Building on its strong 50 year heritage and industry specific expertise, Capgemini enables organizations to realize their business ambitions through an array of services from strategy to operations. Capgemini is driven by the conviction that the business value of technology comes from and through people. It is a multicultural company of 200,000 team members in over 40 countries.
Visit us at www.capgemini.com. People matter, results count.
Role: Big Data & Cloud DevOps Engineer
Location: Toronto, ON.
Type: Full time Permanent with benefits
JOB SPECIFICATIONS AND QUALIFICATIONS:
• 5 years of experience in Spark Hadoop.
• 5 years of experience programming in Java Scala.
• 5 years of experience in Docker, Swarm, Kuberenetes.
• 5 years of experience with Python, Shell Scripting.
• Proficient understanding of distributed computing principles.
• Proficient understanding of networking principles.
• Proficient understanding of performance computing principles.
• Experience with NoSQL, Graph databases such as MongoDB Ignite and Druid.
• Experience with Hadoop, Docker, Kubernetes and ELK Stack a plus.
• Experience with Hive.
• Take ownership of components of the workflows supported within our data ecosystem.
• Interact with CM development teams across and understand their application requirements data access patterns and assist them with expediting onboarding to various platforms from a engineering and development aspect.
• Design and develop systems that meet our latency volume storage and scale expectations to enhance KPI metrics and monitoring capabilities for use across multiple teams.
• Participate in meetings to help influence architectural engineering and development decisions.
• Follow our Agile software development process with daily scrums and monthly Sprints.
• Ability to work collaboratively on a cross functional team with a wide range of experience levels.
• Define best practices for spark usage work with teams to influence their architecture.
• Provide expertise in Spark Performance tuning.
• Perform knowledge sharing, conduction, education workshops and train other employees is expected.
• Keep pace with emerging technology by researching and evaluating products, AUTHORITIES IMPACT RISK.
• Recognized Big Data Cloud DevOps Engineer who can helps build components, drive best practices, standards and provide guidance insight to partnering Architecture, Development, Engineering and Operations teams across QTS.
KEY RELATIONSHIPS – QTS Application Development Teams, QTS Architecture and Engineering Team, QTS Engineering and Operations Team.