Senior Data Platform Reliability Engineer

OpsWerks; Philippines; On-site; PHP 1,200,000 - 2,400,000; Full time

Job summary

OpsWerks in the Philippines seeks a Senior Data Platform Engineer to operate and enhance data platforms on Kubernetes, on-prem and cloud-based (AWS/EKS, GCP/GKE). You will deploy releases with GitOps, monitor health, and drive reliability.

You will lead incident response, mentor juniors, and push for improved observability and automation across data workloads such as Spark, Airflow and Jupyter.

Qualifications

• 5+ years supporting production data workloads and platforms (Spark, Airflow, Jupyter).
• 5+ years ETL/ELT development and data transformations (Python/Java/SQL).
• Practical Kubernetes experience including cloud-managed flavors (AWS-EKS/GCP-GKE).
• Strong Linux, microservices and service communication fundamentals.
• Excellent troubleshooting, logging, metrics and KPI analysis.

Responsibilities

• Operate, maintain and improve company data platforms on Kubernetes (on-prem and cloud).
• Deploy releases and config changes via GitOps/DevOps processes.
• Monitor platform health using logs, metrics and observability tools.
• Participate in incident response, RCA and 24x7 rotations.
• Improve observability, tooling, automation and reliability.
• Troubleshoot user concerns and guide resolutions for issues.
• Provide technical mentorship to junior engineers.

Skills

Data platforms

Kubernetes

ETL/ELT pipelines

Python/Java/SQL

Linux & microservices

Monitoring & observability

Tools

AWS EKS

GCP GKE

GitOps/DevOps

Logging/metrics tools

Job description

As a Senior Data Platform Engineer, you will be responsible for operating, maintaining, and continuously improving the company’s data platforms running on Kubernetes (On-premise and/or on AWS/GCP) - similar on the DoEKS (Data on EKS) / AIoEKS (AI on EKS) deployment frameworks

• Deploy new releases and configuration changes through GitOps/DevOps
• Monitor platform and service health using logs, metrics, and observability tools
• Participate in incident response, root cause analysis and 24x7 operational rotations
• Improve platform observability, operational tooling/automations, self-service capabilities and reliability practices to reduce recurring issues
• Investigate & troubleshoot user concerns by either correlating them to system-related issues, breaking integrations and/or user-specific errors/misconfigurations up to recommending/executing resolutions
• Provide technical mentorship to junior engineers
• Advocate for platform standards, security best practices, and operational excellence

Your Qualifications

• Minimum 5 years of solid experience supporting production data workloads/platforms (Spark/Airflow/Jupyter)
• 5+ years of hands-on experience on ETL/ELT pipeline development & data transformations (Python/Java & SQL)
• Practical proficiency in Kubernetes environments including Cloud-provider managed Kubernetes flavors (AWS-EKS/GCP-GKE)
• Comprehensive knowledge on Linux environments, microservice architectures and service communication patterns
• Strong troubleshooting fundamentals such as application crashes, resource contentions, service latency, and scaling behavior
• Well-rounded competency in analyzing logs, metrics, monitoring systems, and service KPIs

Plus points if you have:

• Exposure in other Data/AI platforms such as Flink, Trino, Druid and Ray.I
• Hands-on experience with automation or scripting (Bash, Python)
• Kubernetes or Data certifications (CKAD, AWS Certified Data Engineer)