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Site Reliability Engineering - Sr. Consultant - PRE

Visa
life insurance, paid time off
United States, Texas, Austin
Nov 11, 2024
Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose - to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

Single window support: Leverage deep understanding of Hadoop and its related tools specially Hive, SPARK, HDFS and do complete RCA be it platform or user code/config related.
System configuration: Recommend necessary changes to the system to DAP platform engineering by checking system activity and user logs for triaging and troubleshooting.
Performance Tuning: Direct team members on crafting efficient queries, leveraging expertise in performance tuning and optimization strategies for big data technologies.
Issue resolution across Tech teams: Troubleshoot and resolve complex technical issues. Identify root causes, finding which Tech/Data platform team can fix it and coordinating among those teams.
Reliability engineering: Creating reports to define performance and resolution metrics for proactively identifying issues and generating alerts.
Office hours and liaising: Calls across regions in multiple time zones to ensure timely client delivery.
Knowledge cataloging and sharing: Share knowledge and cross-train peers across geographic regions using Wikis and communications. Provide comms around issues/outages affecting multiple users.
Develop Standards: The team would prepare standard configuration for a variety of VCA workloads to make the jobs run with optimal settings to maintain good cluster health while executing the jobs efficiently.
Continuous Learning of VCA workload: Continuously learn and stay updated with the changing nature of data science jobs to help improve Cluster utilization.

With active engagement, collaboration, effective communication, quality, integrity, and reliable delivery, develop and maintain a trusted and valued relationship with the team, customers, and business partners.

This is a SRE Role to provide support for Technical hadoop related issues impacting VCA data scientists users on day to day basis. it includes performance tuning, SPARK optimization, Data Availability, Issue triages and user communication.

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

Qualifications

Basic Qualifications:

  • 8+ years of relevant work experience with a Bachelor's Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience.

Preferred Qualifications:

  • 9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD
  • Hands on experience working as a Hadoop system engineer in managing Hadoop platforms.
  • Ability to solve complex production problems and debug code.
  • Strong understanding on data pipelines built using PySpark, Hive, Airflow
  • Experience working with scheduling tools (Airflow, Oozie) or building data processing orchestration workflows.
  • Experience in tuning application performance on Hadoop platforms.
  • Good knowledge on Hadoop eco-system such as Zookeeper, HDFS, Yarn, HIVE and SPARK.
  • Understanding of security tools like Kerberos and Ranger.
  • Hands-on experience in debugging Hadoop issues both on platform and applications.
  • Experience in Managing Data Scientist users and solving/triaging their issues
  • Understanding of Linux, networking, CPU, memory, and storage.
  • Knowledge/Experience in Python.
  • Excellent written and verbal communication skills is a must have.
  • Enjoy working fast and smart, and able to grasp complex concepts and functionalities.
Additional Information

Work Hours: Varies upon the needs of the department.

Travel Requirements: This position requires travel5-10% of the time.

Mental/Physical Requirements: This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.

U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is 143,200.00 to 207,800.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.

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