Responsibilities
Migrate existing UC4 job plans, schedules, and dependencies into Airflow DAGs, preserving legacy behavior and validating parity (timing, dependencies, output)
Identify UC4 capabilities with no native Airflow equivalent (e.g., business calendars, agent-based execution, object-level security) and build the custom operators, hooks, sensors, or timetables needed to close the gap
Extend and maintain the internal migration/conversion tooling that generates Airflow code from legacy definitions
Build and maintain observability for the platform, metrics, Grafana dashboards, and alerting

Required Skills :
Python (robust): clean, testable, reusable code; comfort building reusable component libraries
Apache Airflow: DAG design, custom operators/hooks/sensors, scheduling, retries, pools, XComs, deployment; experience with major Airflow version upgrades (2.x → 3.x) a plus
UC4/Automic: working knowledge of jobs, job plans, schedules, calendars, and agents
SQL / ETL fundamentals
DevOps: Git, CI/CD, Docker/Kubernetes, Linux/shell scripting
Observability: Prometheus and Grafana, building dashboards/alerting from scratch

📌 Airflow Developer Bengaluru
🏢 Flexton
📍 Bengaluru