Staff Site Reliability Engineer - Big Data Platform Engineer(Python/Cloud) at Visa

Austin, Texas, United States

Visa Logo
Not SpecifiedCompensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
FinTech, Payments, TechnologyIndustries

Requirements

  • 5 or more years of relevant work experience with a Bachelor's Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD
  • Preferred: 6 or more years of work experience with a Bachelor's Degree or 4 or more years of relevant experience with an Advanced Degree
  • Expertise in one or more general development languages (e.g., Java, Python) or full stack development
  • Energy and experience: A growth mindset that is curious and passionate about technologies and enjoys challenging projects on a global scale
  • Challenge the status quo: Comfort in pushing the boundaries, “hacking” beyond traditional solutions
  • Learner: Constant drive to learn new technologies
  • Partnership: Experience collaborating with Engineering, Application and other functional teams

Responsibilities

  • Design, build and manage Hadoop and Kafka clusters on Cloud - AWS, GCP and Azure
  • Manage and optimize Open-Source Apache Hadoop, Big Data and Kafka clusters for high performance, reliability, and scalability
  • Develop tools and processes to monitor and analyze system performance and to identify potential issues
  • Collaborate with other teams to design and implement solutions to improve reliability and efficiency of the in-premise Hadoop, Big Data and Cloud platforms
  • Effective root cause analysis of major production incidents and the development of learning documentation
  • Planning and performing capacity expansions and upgrades in a timely manner to avoid any scaling issues and bugs
  • Tune alerting and set up observability to proactively identify issues and performance problems
  • Creating standard operating procedure documents and guidelines on effectively managing and utilizing the platforms
  • Leverage DevOps tools, disciplines (Incident, problem, and change management), and standards in day-to-day operations
  • Concentrate on developing tools and automations using Ansible, Python, Java, or other programming languages

Skills

Python
Hadoop
Kafka
AWS
GCP
Azure
Big Data
Site Reliability Engineering
Cloud
Distributed Systems
Monitoring
Apache Hadoop

Visa

Global digital payment network provider

About Visa

Visa operates a global digital payment network that facilitates electronic payments for millions of people daily. The company connects consumers, businesses, financial institutions, and governments, allowing them to make transactions using Visa cards. Each time a card is used, Visa earns money through transaction, service, and data processing fees. Unlike many competitors, Visa focuses on expanding access to financial services for underserved communities and supporting local economies. The company's goal is to promote financial inclusivity and drive sustainable commerce, ensuring that more people can participate in the global economy.

San Francisco, CaliforniaHeadquarters
1958Year Founded
$55.8MTotal Funding
ANGEL_INDIVIDUALCompany Stage
Fintech, Financial ServicesIndustries
10,001+Employees

Benefits

Health Insurance.
Life Insurance.
Dental Insurance.
Disability Insurance.
Accidental Death & Dismemberment Insurance.

Risks

CBDCs could reduce reliance on Visa's payment network.
'Buy Now, Pay Later' services may decrease traditional credit card transactions.
Fintech startups offering zero-fee transactions could pressure Visa's revenue model.

Differentiation

Visa operates a global digital payment network connecting millions daily.
The company focuses on financial inclusivity and sustainability in its operations.
Visa collaborates with central banks on Central Bank Digital Currencies (CBDCs).

Upsides

Visa's partnership with fintechs enhances cross-border payment solutions.
Adoption of blockchain technology could revolutionize digital payments.
AI-driven fraud detection systems are reducing fraudulent activities.

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