Senior Data Platform Reliability Engineer

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

Job summary

OpsWerks is seeking a Senior Data Platform Engineer to operate, maintain, and improve data platforms running on Kubernetes on‑premise and in the cloud across DoEKS/AIoKS frameworks. You’ll deploy releases, monitor health, and participate in 24x7 rotations while guiding junior engineers toward operational excellence.

You’ll champion platform standards, security best practices, and robust observability, enabling reliable data workloads and scalable analytics for diverse teams.

Qualifications

• 5+ years of production data workloads experience.
• ETL/ELT pipelines in Python/Java/SQL.
• Kubernetes and cloud Kubernetes experience.
• Strong troubleshooting and observability fundamentals.
• Mentor junior engineers and promote platform standards.

Responsibilities

• Deploy releases via GitOps/DevOps.
• Monitor platform health using logs, metrics, and observability tools.
• Participate in incident response and 24x7 rotations.
• Improve observability and self-service tooling.
• Troubleshoot user concerns and propose resolutions.
• Mentor junior engineers and advocate for security/excellence.

Skills

Spark

Airflow

Jupyter

Python

Java

SQL

Kubernetes

Tools

AWS EKS

GCP GKE

Linux

Job description

Job Description:

Your Role

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)

Requirements: