Bachelor's degree in computer science, mathematics, or engineering
5+ years of platform administration experience in hybrid cloud environments (Azure data/analytics platforms, Informatica, BI administration, and application administration)
3+ years hands-on experience as a Platform Engineer in a Big Data environment (Spark, Python, Linux, database management)
2+ years design and implementation experience with large-scale data environments and hands-on experience with building and optimizing data pipelines using CI/CD, DevOps, deployment automation, configuration management, and Unix/Linux scripting; Elasticsearch/Kibana experience is a plus
Requirements:
Build, configure, administer, and deploy DSO data analytics tools and platforms to support the data strategy initiatives in hybrid cloud environments
Collaborate with infrastructure, cloud engineering, TEO, data and enterprise architects to configure, tune, integrate, and optimize platforms to meet functional and technical requirements with a strong emphasis on security, policy adherence, quality, and performance
Work in an agile team, provide status updates in scrum meetings, troubleshoot performance issues, and coordinate with security and risk to deploy applications in distributed platforms while ensuring production readiness in terms of operational, security, and compliance standards
Drive innovation and best practices to create and execute roadmaps that improve efficiencies, agility, performance, and stability of big data and cloud platforms; continually optimize data pipelines with automation and DevOps/Agile methodologies; participate in daily project and production delivery status meetings and provide technical support for faster issue resolution
Responsible for building, configuring, administering, and deploying client's DSO data & analytics tools and platforms to support the data strategy initiatives. These platforms will support development teams to build data & analytic applications for parsing, analyzing, discovering, and visualizing the potential business insights in the hybrid cloud environments. Works with various cross functional teams such as infrastructure, cloud engineering, TEO, data and enterprise architects to configure, tune, integrate, optimize the platform to meet functional and technical requirements. A strong affinity to appreciate and enforce the security and policies, as well as attention to quality and performance are integral parts of the job function. Works in an agile team, provide statuses in scrum meetings, can trouble shoot performance issues, work closely with security and risk to deploy applications in distributed platforms. Ensures the design, code, and procedural aspects of solution are production ready, in terms of operational, security and compliance standards before deployments are done in higher environments. Applies innovation, problem solving and best practices to create and execute road maps that improve efficiencies, agility, performance, and stability, of big data and cloud platforms. Continually optimize the data pipe with automation, and tools with the latest DevOps and Agile methodologies to improve cycle times, consistency, and quality. Participates in day-to-day project and production delivery status meetings and provide technical support for faster resolution of issues.
Bachelor's degree in computer science, Mathematics, or Engineering
5+ years of platform administration experience in different hybrid cloud environments – Azure data and analytics platforms, Informatica, BI administration, Application admins
3+ years of hands-on experience as a Platform Engineer in a Big Data environment (Spark, Python, Linux, Database management)
2+ design and implementation experience with large scale data environments
Professional training and certifications in various cloud data solutions (Preferred).
Deep hands-on experience with administering complex hybrid cloud applications
1+ years of development and operations experience with Elasticsearch and Kibana.
Informatica MDM, DQ, ETL architecture experience is a plus
Hands on experience with building, optimizing the data pipe – CI/CD, DevOps, integrated - build and deployment automation, configuration management, test automation solutions.
