Lead Systems EngineerPrimary SkillsAirflowAutosysPythonGood to haveFinance domain expJD1. Design implement and maintain Airflow DAGs (Directed Acyclic Graphs) to automate ETL (Extract Transform Load) processes and other data workflows.2. Configure and manage task dependencies scheduling retries and error handling in Airflow.3. Integrate Apache Airflow with different data sources processing systems and storage solutions (e.g. databases cloud services data lakes). Responsibility 7 years of experience in managing workflow automation and job scheduling with at least 3 year focused on Apache Airflow.Strong background in Autosys (preferably 3 years) including job scheduling dependency management and error handling.Experience migrating jobs from Autosys to Airflow and automating complex workflows.Familiarity with Airflows components such as operators sensors and hooks.Strong knowledge of Python for writing Airflow tasks and custom operators. Experience working with cloud environments (AWS GCP Azure).Solid understanding of SQL databases and data engineering concepts.Familiarity with containerization technologies (Docker Kubernetes) is a plus.Experience with monitoring alerting and logging systems (e.g. Prometheus Grafana).