Big Data Support Engineer L1
Tookitaki · Manila, Metro Manila, Philippines ·
- Category
- Support
- Experience
- 3+ years
Tookitaki · Manila, Metro Manila, Philippines ·
Location: Manila,Metro Manila,Philippines
Role: Big Data Support Engineer
Job Title: Big Data Support Engineer
Location: PH
Department: Support
Reports to: Head of Support
We are seeking a Technical Support Agent who will play a critical role in maintaining high customer satisfaction by ensuring timely and effective resolution of client issues. This role is essential for Tookitaki's support services, catering to both on-premise and cloud-hosted (CaaS)clients. You will work closely with cross-functional teams to manage daily support issues, adhere to SLAs, and contribute to the continuous improvement of our customer support processes.
The ideal candidate will have a strong understanding of Tookitaki's product and tech stack, the ability to triage issues effectively, excellent client management skills, and fluency in English. Knowledge of Cantonese is a plus.
Key Responsibilities:
Client Support Management
Collaboration and Escalation
Technical Expertise and Triage
Client Management and Communication
Continuous Improvement and Documentation
Rotational Shifts and Availability
Qualifications & Skills
Own customer incidents, service requests, and change requests through Freshworks or equivalent ticketing platforms.
• Troubleshoot production issues affecting Spark jobs, Kubernetes workloads, Kafka pipelines, Elasticsearch clusters, APIs, and cloud infrastructure.
• Ensure all customer issues are resolved within SLA while maintaining high customer satisfaction.
• Perform root cause analysis (RCA) and document preventive actions.
• Monitor health and performance of Spark applications running on Kubernetes.
• Investigate failed Spark jobs, executor failures, pod crashes, resource contention, and scheduling issues.
• Monitor Kafka topics, brokers, consumer groups, lag, and message delivery.
• Support Elasticsearch cluster health, indexing pipelines, shard allocation, and search performance.
• Perform production validations after deployments and infrastructure upgrades.
• Participate in planned maintenance activities, upgrades, and release support.
• Diagnose issues across the complete cloud-native stack including Apache Spark on Kubernetes, Apache Kafka, Kubernetes (Pods, Deployments, Services, ConfigMaps, Secrets), Docker Containers, AWS Infrastructure, Elasticsearch, Airflow Workflow Orchestration, Hive / Trino / SQL-based Data Processing, REST APIs and Microservices, Linux-based Production Systems.
• Work closely with Product Engineering to identify software defects and Infrastructure teams to resolve
platform-related issues.
• Coordinate with Product Engineering for bug fixes and product improvements.
• Work closely with Infrastructure teams during production incidents.
• Support onboarding teams during production go-live and customer transition.
• Participate in Major Incident Management (P1/P2).
• Provide timely updates to customers during incidents.
• Communicate technical issues in a clear and business-friendly manner.
• Maintain ownership until issue closure.
• Prepare incident summaries, RCA documents, and customer communications.
• Create and maintain SOPs, troubleshooting guides, and knowledge base articles.
• Identify recurring issues and recommend automation opportunities.
• Improve monitoring, alerting, and operational processes.
• Contribute to platform reliability and operational excellence initiatives.
• Participate in 24x7 production support rotation.
• Provide support during scheduled maintenance windows, infrastructure upgrades, and customer go-lives.
• Support weekend deployment activities when required.
TECHNICAL SKILLS
Apache Spark (Spark on Kubernetes preferred) ,Kubernetes, Apache Kafka, Elasticsearch
AWS Services (EC2, EKS, S3, IAM, CloudWatch), Docker, Airflow, Hive / Trino, Linux Administration
Prometheus, Grafana, Kibana, Elasticsearch Monitoring, CloudWatch, Kubernetes Logging & Monitoring
Log Analysis and Production Diagnostics, Strong SQL knowledge, Understanding of distributed systems architecture, Knowledge of networking fundamentals.
Experience using REST APIs
Familiarity with Git and CI/CD concepts
Ability to analyze application logs and distributed system failures
Understanding of resource management, autoscaling, and Kubernetes scheduling
Excellent written and verbal English communication
Strong stakeholder management
Ability to communicate technical concepts to non-technical users
Experience managing customer escalations
Mandarin (spoken and written) is preferred
Cantonese is an added advantage
Strong analytical and troubleshooting skills
Ability to work under pressure during production incidents
Prioritize incidents based on business impact
Perform structured RCA and recommend preventive measures
Experience working with SLA-driven support environments
Familiarity with ITIL incident management processes
Strong documentation practices
Experience using Freshworks, Jira, ServiceNow, or similar platforms
EXPERIENCE
3–6years of experience supporting large-scale production systems. Experience supporting cloud-native applications
running on Kubernetes. Hands-on production support experience with Spark,Kubernatives, Kafka, Elasticsearch, and AWS.
Experience in Financial Services, FinTech, RegTech, SaaS, or Big Data platforms is highly desirable.