Description

You will design, build, and manage complex, scalable batch processing pipelines using Java and Apache Airflow.

This role is on-site.

Responsibilities

• Develop and maintain complex DAGs in Apache Airflow, including writing custom operators, hooks, and plugins.
• Lead migrations from legacy scheduling systems, specifically Autosys, to cloud-native orchestration platforms like AWS MWAA.
• Implement and troubleshoot highly scalable, fault-tolerant batch pipelines using Spring Batch and Java.
• Manage and secure Airflow environments on AWS MWAA, handling setup, configuration, and scaling.
• Diagnose and resolve complex technical issues across the pipeline ecosystem.

Required Skills

• 10+ years of professional experience in Java/JEE and RDBMS databases.
• 5+ years of hands-on experience with Spring Boot and Spring Batch.
• 5+ years of experience with Apache Airflow, including DAG development and custom components.
• 5+ years of Python programming experience for Airflow DAG development.
• 3+ years of experience with Autosys, covering job scheduling and administration.
• Expert-level experience with AWS Managed Workflow for Apache Airflow (MWAA).
• Extensive experience with AWS cloud services (e.g., CloudWatch, IAM).
• Experience with relational (PostgreSQL, Oracle) and NoSQL databases (DynamoDB, MongoDB).

Key Skills

Education

Any Graduate