Big data Admin

Wipro; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

Wipro is seeking an experienced Big Data Platform Engineer in Singapore to lead and support Hadoop ecosystems including Kafka, HDFS, and AWS EMR. The role emphasizes production readiness, security, and high-availability for payment-related data systems.

You will work across teams to drive improvements, mentor staff, and ensure the scalable, reliable operation of large data pipelines in a fast-paced environment.

Qualifications

• 13-15 years of Big Data / Data Platform Engineering experience in enterprise environments.
• Strong hands-on with Kafka, AWS EMR, Linux scripting and Kerberos.
• Experience in high-volume, low-latency systems (payments/trading preferred).
• Ability to lead technical issues, coach teams and drive RCA and improvements.

Responsibilities

• Takes up technical tasks and delegates issues within the team.
• Supports production readiness and incident management across Hadoop ecosystems.
• Maintains secure access and runbooks; ensures 24x7 availability of critical systems.
• Engages with stakeholders to align technology roadmaps and projects.

Skills

Hadoop Admin

Kafka Admin

Shell/Python

Kerberos security

Linux admin

AWS EMR

SQL Hive

JVM knowledge

Data security

Tools

HDFS

YARN

OpenSearch

Job description

As a L3 resource of his /her team, he /she:

• Takes up technical tasks and also manages delegation for technical issues within the team,
• animates the team to encourage collaboration and sharing of best practices,
• supports new technologies and leverages them to provide consistency of service across streams,
• proposes service improvements for all Big Data services supported throughout the organization,
• documents, reviews, maintains and shares relevant technical information within the team
• provides technical knowledge, supports services both proactively and reactively to maintain the availability and reliability of system infrastructure in accordance to the SLA,
• works in line with policies based on LEAN-CA-CIB best practices,
• Actively engages during any high severity issue and drives for issue resolution.
• reviews technology changes to identify potential risks,

As an experienced professional in Big Data Services, he/she:

• supports his/her team during diagnosis when technical issues rise in his/her scope of expertise,
• is aware of the global IT structure so that he/she anticipates interrelationships within the organization,
• engages with technical peer, Development team, Service managers, Architect and project teams on technology roadmap and projects,
• facilitates transformation projects and suggest future directions for new areas of improvement and change,
• guarantees the production readiness and license to operate of new projects and solutions
• is available and able to drive technically, any complex or high severity incidents that occur within the scope of their role
• actively engages to understand new technologies and technology trends and reviews them with a view to incorporating them into CACIB operations
• actively assists in identifying the most technical skilled candidates for open roles,
• technically coach and develop partner resources to improve quality and productivity,

Candidate profile

Mandatory track record

• Excellent working knowledge of Hadoop ecosystem (Hadoop, Hive, Pig, Oozie, Hbase, Flume, sqoop) using both automated tool sets as well as manual processes.
• Support and maintain Hadoop (HDP) clusters for batch processing, analytics, and regulatory reporting.
• Perform Hadoop cluster lifecycle management: provisioning, scaling, patching, and decommissioning nodes.
• Ensure 24x7 availability and resilience of production systems supporting payment flows.
• Manage and optimize Apache Kafka for high-throughput, real-time payment event streaming.
• Ensure data consistency and fault tolerance across streaming pipelines.
• Support Apache NiFi for ingestion pipelines from upstream payment systems and external partners.
• Work with AWS EMR for scalable processing of transaction data and reconciliation workloads.
• Administer HDFS, ensuring optimal replication, storage utilization, and fault tolerance.
• Monitor and tune MapReduce and YARN workloads to handle large‑scale transaction data efficiently.
• Ensure proper configuration and validation of jobs handling payment clearing, settlement, and reporting.
• Manage OpenSearch / Elasticsearch clusters for transaction search, audit trails, and operational dashboards.
• Excellent working knowledge of Elastic Kibana and making pipelines to capture and search relevant data.
• Optimize indexing and query performance for near real‑time analytics and monitoring.
• Implement Kerberos‑based authentication and secure access controls across the Hadoop ecosystem.
• Manage user provisioning (Linux + Hadoop stack) ensuring least‑privilege access.
• Ensure compliance with banking regulations, audit requirements, and data governance policies.
• Monitor cluster security, encryption, and network connectivity.
• Conduct capacity planning aligned with transaction growth and peak payment volumes.
• Optimize systems for low latency and high throughput, critical for digital payments.
• Identify bottlenecks and implement performance tuning strategies across platforms.
• Ensure high availability through failover mechanisms, DR strategies, and proactive monitoring.
• Develop and maintain runbooks, SOPs, and architecture documentation.
• Define and enforce best practices for cluster operations, deployments, and data pipelines.
• Contribute to continuous improvement initiatives and knowledge sharing.
• Excellent communication, interpersonal and logical skills
• Customer service oriented and a strong team player
• Ability to work under pressure and a commitment to solving issues

Required Skills & Experience

• 13-15 years of experience in Big Data / Data Platform Engineering in enterprise environments.
• Strong hands‑on experience with:
  • Apache Kafka (high‑throughput environments)
  • AWS EMR + good knowledge of AWS Cloud.
  • Strong expertise in Linux system administration and scripting (Shell/Python)
  • Experience with Kerberos, data security, and access governance
  • Proven experience in handling high‑volume, low‑latency systems (preferably payments/trading)

Work Schedule

• Work schedule is mainly focused to support Asia and EMEA (Paris) time zone; however, may have to support during non‑office hours/weekends/public holidays for critical incidents or escalation as per the assigned on‑call support requirements;

Work Hours:

9:00 AM to 6:00PM(Sing Shift) or 2PM to 11PM (Paris Shift).

Skills Must/Good to have

• Hadoop Administration(HDFS, YARN , STORM , HBASE and other components) Must
• Kafka Adminstration and good knowledge of kafka internals Must
• Scripting Knowledge(any language but preferably shell, perl or python) Must
• AWS cloud certification Good to have
• Knowledge of Access control and security mechanisms like PAM and Kerberos Good to have
• Hardware Configurations and setup like racks, disk topology and RAID Good to have
• Knowledge of Virtual Machines(deployment & configuration) Good to have
• Knowledge of JVM Good to have
• Proficiency in Python, Java, or Scala Proficiency in SQL, Hive or another SQL-on-Hadoop tool Good to have
• Experience with ETL process/software Good to have