Urgent Opening for Data Orchestration Engineer

We are seeking an experienced Data Orchestration Engineer to lead the migration from AutoSys to Apache Airflow and establish a modern, scalable enterprise orchestration platform. This role will focus on migrating legacy workloads, automating data pipelines, improving reliability, and standardizing orchestration across our enterprise technology ecosystem.

Key Responsibilities

• Lead the migration of enterprise workloads from AutoSys to Apache Airflow, including job discovery, dependency mapping, conversion, testing, and cutover.
• Design, develop, and maintain Apache Airflow DAGs for data pipelines and enterprise workflows.
• Assess existing AutoSys scheduling patterns and identify opportunities to consolidate, simplify, or eliminate legacy jobs.
• Orchestrate workloads across Databricks, Microsoft Fabric, cloud services, APIs, and enterprise applications.
• Establish standards for scheduling, dependencies, retries, error handling, monitoring, and operational recovery.
• Implement CI/CD, version control, and infrastructure-as-code practices for orchestration.
• Partner with data engineering, application development, and platform teams to ensure migration continuity and minimize operational disruption.

Required Qualifications

• 5+ years of experience in data engineering, platform engineering, or enterprise workload orchestration.
• Hands-on experience with AutoSys and Apache Airflow, including migration of legacy enterprise scheduling workloads to modern orchestration platforms.
• Strong Apache Airflow expertise, including DAG development, operators, sensors, scheduling, and production operations.
• Proficiency in Python, SQL, and REST APIs.
• Experience with cloud platforms (Azure, AWS preferred), Databricks, and modern data architectures.
• Understanding of CI/CD, containerization, observability, and production support.

Success Measures

• Successful migration and retirement of AutoSys workloads with minimal business disruption.
• Reduction in legacy job complexity and manual intervention.
• Improved reliability, observability, and recovery of enterprise workflows.

Standardized, reusable orchestration patterns that accelerate future development.