SR. Data Platform Reliability Engineer/SRE DevOps/Data Engr. (Permanent)- Onsite

ATS CONSULTING SERVICES PH INC.; Mandaluyong; On-site; PHP 1,800,000 - 2,400,000; Full time

Job summary

ATS CONSULTING SERVICES PH INC. is seeking a Senior Data Platform Engineer to operate, maintain, and enhance our data platforms on Kubernetes, both on‑premises and in AWS/GCP. You will work on DoEKS‑like deployments and help drive reliability and observability across the stack.

Responsibilities include deploying releases via GitOps, monitoring health, incident response, and mentoring junior engineers while promoting security and best practices in platform engineering.

Qualifications

• 3+ years supporting production data workloads (Spark, Airflow, Jupyter).
• 5+ years ETL/ELT development and data transformations (Python/Java/SQL).
• Proficient in Kubernetes environments, incl. EKS/GKE.
• Strong Linux knowledge; microservices and inter-service communication.
• Troubleshooting crashes, contention, latency, and scaling.
• Skilled in analyzing logs, metrics, and KPIs.
• Exposure to Flink, Trino, Druid, Ray.
• Automation/scripting with Bash and Python.
• CKAD and AWS Certified Data Engineer certifications.

Responsibilities

• Deploy releases and configuration changes via GitOps/DevOps.
• Monitor platform health with logs, metrics, and observability tools.
• Participate in incident response, root cause analysis, and 24x7 rotations.
• Improve observability, tooling, self-service capabilities, and reliability practices.
• Investigate and troubleshoot user issues and recommend resolutions.
• Provide technical mentorship to junior engineers.
• Advocate for platform standards, security best practices, and operational excellence.

Skills

Spark

Airflow

Jupyter

Python

Java

SQL

Kubernetes

Linux

Bash

CKAD

AWS Certified Data Engineer

Git

CI/CD

Tools

Git

CI/CD

Job description

About the 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.

Key responsibilities

• 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

About you

• 3+ 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
• Exposure in other Data/AI platforms such as Flink, Trino, Druid and Ray
• Hands-on experience with automation or scripting (Bash, Python)
• Kubernetes or Data certifications (CKAD, AWS Certified Data Engineer)