Infrastructure Engineering Senior Engineer #1038419
Job Description:

• Employees part of this function are responsible for building and operating IT hardware and software resources in on-prem, cloud or hybrid scenarios in support of internal customer needs.
• They are responsible for a wide variety of activities that operationalize cross functional teams such as capacity planning and resource optimization solutions for one-off and long-term workloads, planning, configuring and maintaining servers (including mainframes), creating virtualized environments, providing analytics services, installing and maintaining specialized tools, etc

 
Key Responsibilities

• Involved in the design, operation, and maintenance of enterprise servers, including specialty mainframe systems like IBM/LPARS, high performance super computing systems, and general-purpose hybrid and cloud systems, for optimal end-user business operations.
• Research, design, implement and maintain complex infrastructure solutions for internal customer needs such as specialty software, data warehouses, identity access management, event frameworks, containerization and on demand scaling, etc.
• Design and configure secure virtualized environments aligned with enterprise architecture blueprints consisting of virtual machines, virtual networks, high speed and distributed storage systems (SAN, HDFS, SSD, etc.)
• Utilize existing tools or assist in engineering custom monitoring solutions to ensure systems are configured correctly, run efficiently and remain secure against potential threats.
• Monitor and review resources like CPU, memory, storage, and network traffic to ensure effective utilization aligned with expected parameters and to safeguard against runaway costs.
• Resolve bottlenecks and plan for future capacity needs based on resource usage trends.
• Advise enterprise architecture teams on usage trends to incorporate into future blueprints.

 
Skills Required:

• Informatica

 
Skills Preferred:

• Cloud Infrastructure

 
Experience Required:

• Senior Engineer Exp: Prac. In 2 coding lang. or adv. Prac. in 1 lang.; guides.
• 10+ years in IT; 8+ years in development

 
Experience Preferred:
Summary of Responsibilities:

• Engineer, test, and modernize data management platforms primarily Informatica Enterprise Data Catalog and Apache NiFi.
• Enable cloud migrations for Analytics platforms Define, document, and monitor global (Follow-the-Sun) support procedures (Incident Management, Request Management, Event Management, etc). Provide Asia-Pacific (IST) 2nd level support for these products.

 
Responsibilities Detail:

• Installing and configuring products, Working with platform teams support to resolve issues, Working with vendor support to resolve issues,
• Thoroughly testing product functionality on the platform;
• Developing custom installation guides, configurations, and scripts that are consistent with IT security policy;
• Providing 2nd level support regarding product related issues;
• Developing new tools and processes to ensure effective implementation and use of the technologies.
• Implementing, monitoring/alerting, and analyzing usage data to ensure optimal performance of the infrastructure.
• Maintaining a SharePoint site with relevant documentation, FAQs, processes, etc. necessary to promote and support the use of these technologies.
• Required Skills Ability collect and clearly document requirements.
• Ability to prioritize work and manage multiple assignments.
• Ability to create & execute detailed project plans and test plans.

 
Education Required:

• Bachelor's Degree

 
Education Preferred:

• Bachelor's Degree

 
Additional Information :
Experience Preferred Security: Implementing and maintaining security measures for the data management platforms, including access control, data encryption, and vulnerability management.
Performance Optimization: Continuously monitoring and optimizing the performance of the platforms, identifying and resolving bottlenecks.
Automation: Developing and implementing automation scripts and tools to streamline tasks and reduce manual effort.
Collaboration with Other Teams: Working closely with other teams, such as data scientists, data analysts, data engineers and other business stakeholders, to understand their needs and ensure the platforms meet their requirements.