MAP Support Engineer
3 days ago
Role : MAP ( Managed Airflow Platform) Support Engineer
Exp Years
Shift - Night Shift in 2 slots ( 7 PM - 7 AM )
Mandatory Skills : AWS - Cloud platform, Rest API, Apache Airflow, Python & Kubernetes with good communication.
Notice Period : Strictly max 10-15 days
Scope and Responsibilities :
As a Senior Engineer with a focus on Managed Airflow Platform (MAP) support engineering, you will :
- Evangelize and cultivate adoption of Global Platforms, open-source software and agile principles within the organization
- Ensure solutions are designed and developed using a scalable, highly resilient cloud native architecture
- Ensure the operational stability, performance, and scalability of cloud-native platforms through proactive monitoring and timely issue resolution
- Diagnose infrastructure and system issues across cloud environments and Kubernetes clusters, and lead efforts in troubleshooting and remediation
- Collaborate with engineering and infrastructure teams to manage configurations, resource tuning, and platform upgrades without disrupting business operations
- Maintain clear, accurate runbooks, support documentation, and platform knowledge bases to enable faster onboarding and incident response
- Support observability initiatives by improving logging, metrics, dashboards, and alerting frameworks
- Advocate for operational excellence and drive continuous improvement in system reliability, cost-efficiency, and maintainability
- Work with product management to support product / service scoping activities
- Work with leadership to define delivery schedules of key features through an agile framework
- Be a key contributor to overall architecture, framework and design of global platforms
Required Qualifications :
- Bachelor's or Master's degree in Computer Science or a related field
years of experience in large-scale production-grade platform support, including participation in on-call rotations
years of hands-on experience with cloud platforms like AWS, Azure, or GCP
years of experience developing and supporting data pipelines using Apache Airflow including :
- DAG lifecycle management and scheduling best practices
- Troubleshooting task failures, scheduler issues, performance bottlenecks managing and error handling
- Strong programming proficiency in Python, especially for developing and troubleshooting RESTful APIs
- Working knowledge of is considered an added advantage
years of experience in observability using the ELK stack (Elasticsearch, Logstash, Kibana) or Grafana Stack
years of experience with DevOps and Infrastructure-as-Code tools such as GitHub, Jenkins, Docker, and Terraform
years of hands-on experience with Kubernetes, including managing and debugging cluster resources and workloads within Amazon EKS
- Exposure to Agile and test-driven development a plus.
- Experience delivering projects in a highly collaborative, multi-discipline development team environment
Desired Qualifications :
- Experience with participating in projects in a highly collaborative, multi-discipline development team environment
- Exposure to Agile, ideally a strong background with the SAFe methodology
- Skill set on any monitoring or observability tool will be a value add.
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