Location: Manila or Cebu (Onsite)

About OpsWerks

OpsWerks is a technology consulting company specializing in cloud operations, platform engineering, and infrastructure modernization. We help leading organizations build, operate, and scale mission-critical platforms across multi-cloud environments, enabling reliable application delivery, seamless migrations, and operational excellence.

About the Role

We are looking for a Senior Data Platform Reliability Engineer to join our growing team. In this role, you will be responsible for operating, maintaining, and continuously improving large-scale data platforms running on Kubernetes across on-premises and cloud environments (AWS/GCP).

You will work closely with platform, infrastructure, and data engineering teams to ensure platform reliability, performance, scalability, and security while supporting modern data and AI workloads.

Key Responsibilities

• Manage and support production-grade data platforms running on Kubernetes (On-Prem, AWS EKS, or GCP GKE)
• Deploy platform releases, infrastructure updates, and configuration changes through GitOps and DevOps practices
• Monitor platform health, availability, and performance using observability, logging, and monitoring tools
• Participate in incident management, root cause analysis (RCA), and 24/7 operational support rotations
• Diagnose and resolve platform, integration, and user-related issues while implementing preventive measures
• Develop and enhance automation, operational tooling, and self-service capabilities to improve platform reliability
• Optimize platform observability, scalability, resilience, and operational efficiency
• Collaborate with cross-functional teams to ensure successful platform operations and service delivery
• Mentor junior engineers and promote engineering best practices
• Advocate for security standards, platform governance, and operational excellence

Qualifications

Required Skills & Experience

• At least 5 years of experience in ETL/ELT development, data engineering, or data platform operations
• Minimum 3 years of experience supporting production data platforms and workloads such as Spark, Airflow, and Jupyter
• Strong hands-on experience with Python, Java, and SQL
• Practical experience administering Kubernetes environments, including AWS EKS and/or Google GKE
• Strong knowledge of Linux systems, microservices architecture, and distributed systems
• Experience troubleshooting application failures, resource bottlenecks, service latency, and scaling issues
• Proficiency in analyzing logs, metrics, monitoring systems, and operational KPIs
• Strong problem-solving, communication, and stakeholder management skills

Nice-to-Have Qualifications

• Experience with modern data and AI platforms such as Flink, Trino, Druid, Ray, or similar technologies
• Hands-on scripting and automation experience using Python and/or Bash
• Cloud, Kubernetes, or Data Engineering certifications such as:
• CKAD (Certified Kubernetes Application Developer)
• AWS Certified Data Engineer
• Google Professional Data Engineer
• Other relevant cloud-native certifications