Sound knowledge on managing large scale Hadoop platforms including monitoring the platform, debugging issues, and tuning the performance of the cluster.
In-depth knowledge of the Hadoop ecosystem, including Zookeeper, HDFS, Yarn, HIVE, SPARK, Trino and Kafka.
Proven experience in debugging issues on both Hadoop platform and applications.
Familiarity with security tools such as Kerberos, Ranger, and active directory integrations.
Experience on Cloud technologies preferably AWS EMR.
Knowledge on Kubernetes, AI, MLOPS will be advantageous.
Collaboration and Teamwork:
Collaborate closely with L-3 teams to review new use cases and implement cluster hardening techniques, ensuring the development of robust and reliable platforms.
Foster cross-team collaboration, building and maintaining strong relationships with customer teams, user communities, architects, and engineering teams.
Work jointly on key deliverables to ensure production scalability and stability.
Automation: Hands-on Experience with automations using Ansible, Shell, python, or any programming languages. The ability to automate the manual tasks is key in this role.
Observability: knowledge on observability tools like Grafana, opera, Prometheus and Splunk.
Linux: understanding of Linux, networking, CPU, memory, and storage.
Programming Languages: Knowledge of and ability to code or program in one of python, Java or a widely used coding language.
Communication: Excellent interpersonal skills, along with superior verbal and written communication abilities.
This position is not ideal for a Hadoop developer.
This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.
requirements-expected :
Basic Qualifications:
- As a Staff Site Reliability Engineer, you will play a key role in maintaining and supporting Visa’s Data Platform, ensuring the reliability and performance of critical Big Data systems.
- You will drive innovation for our partners and clients globally by working on open-source Big Data clusters, optimizing their availability, efficiency, and scalability.
Education & Experience:
- Master’s degree in Math, Science, Engineering, Computer Science, Information Systems, or a related field; OR
- Bachelor’s degree in Math, Science, Engineering, Computer Science, Information Systems, or a related field, AND a minimum of five years of relevant experience; OR
- A minimum of five years of experience working with Hadoop systems.
Preferred Qualifications:
- Experience in Big Data SRE and Engineering across open-source platforms such as Hadoop, Kafka, HBase, and Spark, with strong troubleshooting and debugging skills.
- Proven ability to conduct effective root cause analysis of major production incidents, document findings, and implement high-availability solutions for critical services.
- Expertise in capacity planning, system expansions, and timely upgrades to mitigate scaling challenges, while automating repetitive tasks to reduce manual effort and prevent errors.
- Ability to fine-tune alerting and set up observability tools to proactively identify and resolve performance issues, collaborating with Level-3 teams on use case reviews and cluster hardening.
- Strong documentation skills to create standard operating procedures and platform utilization guidelines, ensuring consistency and efficiency in operations.
- Proficiency in leveraging DevOps tools and industry best practices, including incident, problem, and change management disciplines.
- Commitment to ensuring Hadoop platform performance meets service-level agreements, with experience in security remediation, automation, and self-healing implementations.
- Experience in developing automation tools and reports to streamline processes, using technologies such as Shell scripting, Ansible, Python, or other programming languages.
