Senior Data Platform Reliability Engineer

Hammerjack Pty Ltd; Philippines; On-site; PHP 1,200,000 - 2,400,000; Full time

Job summary

Hammerjack Pty Ltd is seeking a Senior Data Platform Engineer to operate, maintain, and improve data platforms running on Kubernetes (on-premise and/or AWS/GCP). You will deploy releases through GitOps, monitor health, participate in incident response, and drive reliability.

You will mentor junior engineers, advocate for platform standards and security, and work across data workloads (Spark, Airflow, Jupyter) with a strong Linux background.

Qualifications

• 5+ years of experience supporting production data workloads (Spark, Airflow, Jupyter).
• 5+ years in ETL/ELT development and data transformations (Python/Java & SQL).
• Hands-on Kubernetes in cloud/on-prem environments (AWS-EKS, GCP-GKE).
• Strong Linux, microservices, and service communication knowledge.
• Proven troubleshooting of crashes, contention, latency, and scaling.
• Experience with logs, metrics, and KPIs for observability.

Responsibilities

• Operate, maintain and improve data platforms on Kubernetes (on-prem and cloud).
• Deploy releases and config changes via GitOps/DevOps pipelines.
• Monitor platform health using logs, metrics and observability tools.
• Participate in incident response and root-cause analysis, rotating on-call.
• Improve tooling, self-service capabilities and reliability practices.
• Troubleshoot user and system issues and implement fixes.
• Provide technical mentorship to junior engineers and promote standards.

Skills

Kubernetes administration

Data pipelines

ETL/ELT

Python

Java

SQL

Spark

Airflow

Jupyter

Linux

Troubleshooting

Observability

Bash

CKAD

AWS

GCP

Flink

Trino

Druid

Ray

Tools

Spark

Airflow

Jupyter

Kubernetes

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)