Staff Cloud Infrastructure Engineer - Data Analystics & Intelligence - REF14349G

  • Singapore
  • Full-time

Company Description

Common Purpose, Uncommon Opportunity. Everyone at Visa works with one goal in mind – making sure that Visa is the best way to pay and be paid, for everyone everywhere. This is our global vision and the common purpose that unites the entire Visa team. As a global payments technology company, tech is at the heart of what we do: Our VisaNet network processes over 13,000 transactions per second for people and businesses around the world, enabling them to use digital currency instead of cash and checks. We are also global advocates for financial inclusion, working with partners around the world to help those who lack access to financial services join the global economy. Visa’s sponsorships, including the Olympics and FIFA™ World Cup, celebrate teamwork, diversity, and excellence throughout the world. If you have a passion to make a difference in the lives of people around the world, Visa offers an uncommon opportunity to build a strong, thriving career. Visa is fueled by our team of talented employees who continuously raise the bar on delivering the convenience and security of digital currency to people all over the world. Join our team and find out how Visa is everywhere you want to be.

Job Description

Visa's Distributed Systems Architecture & Engineering (DSAE) team collaborates with product development teams, and other teams within Operations & Infrastructure organization on engineering, building and maintaining the most innovative, reliable, secure and cost-effective distributed solutions to meet VISA customers’ growing needs. 

If you're passionate about and experienced with cloud and containerization, you can be part of DSAE Cloud Infrastructure Engineering Team, which is responsible for the private cloud environment and associated infrastructure management solutions at Visa, specifically in designing and deploying multi-hypervisor based cloud and Kubernetes based container platforms. Knowledge and experience with infrastructure focused data analytics (data modeling, predictive analysis, failure pattern classification and recognition) is one of the key requirements, the other is the ability to establish and automate data analytics workflows to lower the barrier for data driven decision making and democratize data analysis & machine learning. Prior experience with data virtualization, modeling large data sets, and building and applying heuristic AI/Expert systems is required. The successful candidate will work with a team of experienced Cloud Infrastructure & Tools engineers in managing, enhancing and developing Visa’s suite of infrastructure management solutions in support of Visa’s business, projects and team goals through tools automation. 

Specific Responsibilities will include:

  • Design and implement agile innovative infrastructure solutions/infrastructure management solutions that take advantage of technology advances that allow cost reduction, standardization and commoditization

  • Capture, store, prepare and analyze data sets pertinent to infrastructure, application and business services, Assess the effectiveness and accuracy of new data sources and data gathering techniques

  • Add application and service context to infrastructure data sets, draw correlation between user experience, application performance to underline infrastructure, spot degradation and predict potential future failures to enable proactively problem resolution and minimize down time   

  •  Analyze and manifest infrastructure failure patter, implement predictive analysis and trending analysis to improve service availability and reduce Mean Time to Repair(MTTR)

  • Develop processes and tools to monitor and analyze model performance and data accuracy

  • Design, implement and integrate management solutions to effective manage private cloud implementation(Docker, Kubernetes) at Visa’s data centers across the globe, ensure reliability, elasticity and security

  • Provide highly reliable infrastructure management solutions that are extremely secure enabling Operations to manage environments simply and effectively

  • Evaluate, select, initiate, lead and execute the implementation of infrastructure management solutions, ensure on time, on budget, and quality delivery

  • Champion the adoption of open infrastructure management solutions that are fit for purpose yet forward the Visa goals to keep technology relevant

  • Work closely with geographically distributed teams on technical challenges and process improvements

  • Continuously improve tooling, technologies and data analytics capabilities, maintain a common documentation library of standardized procedures, configurations and methodology

  • Evangelize our solution and capabilities, gain insights of the workflows of Product Development, Engineering and Operations teams, ensure relevance and drive adoption

Qualifications

Qualifications:

  • 5+ years of experience manipulating data sets and building statistical models, has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field. Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, etc.

  • Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets

  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.

  • Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Mango, MySQL, etc.

  • Experience visualizing/presenting data for stakeholders using: Tableau, Splunk Dashboards and Graphna. etc.

  • Solid system administration capabilities with good understanding of virtualization (VSphere, Hyper-V) , containerization(Docker) & cloud(Openshift & Kubernetes), and their associated management challenges and possible solutions

  • Clear understanding of modern network protocols and processes running on each of network layers, ready to troubleshoot and diagnosis network/firewall related issues

  • Experience in selecting, designing and developing a tool-chain with loosely coupled software components to perform specific technical functions.

  • Experienced in building automated solutions through tools and software that enable infrastructure to be remotely provisioned, configured and decommissioned

  • Strong analytical skills, able to work independently to solve complex engineering problems. Make independent judgments/decisions within established guidelines

  • Communicate well with others both verbally and in writing and be able to effectively interact with  peers, management and other outside contacts

  • The ability to gather and understand business requirements, translate them into technical/operational requirements

  • High degree of initiative and sense of urgency, comfortable with ambiguity as needs change on a regular basis

  • Self-confident, commands technical authority and respect at all levels

  • Demonstrable teamwork attitude, ready to initiate collaboration and resolve conflicts

 

Key skills required: (in the order of priority)

  • R, Python

  • Data modeling

  • TensorFlow, neural networks, machine learning

  • RHEL Linux & Windows (must have)

  • Good Understanding of network concepts, management protocols (must have)

  • XML, JSON and their transformation (must have)

  • Splunk, ELK, Hadoop, Kafka

  • Bladelogic, SCCM,  Ansible, Chef or Puppet for managing medium & large environments (good to  have)

  • Patrol, SCOM, Zabbix, Nagois for monitoring systems and applications(good to have)

  • API and RESTful principles, able to utilize REST APIs for integration and testing(must have)

  • Version control – Git or Subversion (must have)

  • Containerization, Clustering and scheduling suites such as Kubernetes, Docker UCP (good to have)

 

Additional Information

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