Overview
On Site
Depends on Experience
Full Time
Able to Provide Sponsorship
Skills
Java
Apache Airflow
Airflow
JEE
RDBMS
Spring Boot
Spring Batch
DAG development
custom Airflow operators
Airflow hooks
Airflow plugins
Autosys
job scheduling
Autosys administration
AWS MWAA
AWS Managed Workflows for Apache Airflow
Python
AWS CloudWatch
AWS IAM
AWS cloud services
PostgreSQL
Oracle
DynamoDB
MongoDB
NoSQL
CI/CD
Jenkins
GitLab CI
AWS CodePipeline
batch pipelines
scalable architecture
fault-tolerant systems
legacy tool migration
cloud-native orchestration
troubleshooting
problem-solving
Job Details
- 10+ years of overall professional experience in Java/ JEE and RDBMS databases, and software development.
- 5+ years of hands-on experience in Springboot and Spring batch
- 5+ years of hands-on experience specifically with Apache Airflow, including complex DAG development, custom operators/hooks, and plugin creation.
- 3+ years of hands-on experience with Autosys, demonstrating a solid understanding of its features, job scheduling, and administration.
- Proven track record of successfully leading and executing migrations from legacy scheduling tools (specifically Autosys) to cloud-native orchestration platforms like AWS MWAA.
- Demonstrable expert-level experience with AWS Managed Workflows for Apache Airflow (MWAA), including environment setup, configuration, scaling, security, and troubleshooting.
- 5+ years of hands-on experience in Python programming for Airflow DAG development.
- Extensive experience with AWS cloud services, including but not limited to CloudWatch, and IAM.
- Proven experience designing and implementing highly scalable and fault-tolerant batch pipelines.
- Experience with relational and NoSQL databases (e.g., PostgreSQL, Oracle, DynamoDB, MongoDB).
- Familiarity with CI/CD practices and tools (e.g., Jenkins, GitLab CI, AWS CodePipeline).
- Strong problem-solving skills and the ability to diagnose and resolve complex technical issues, especially during migration.
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