Application Developer- Airflow / Astronomer Migration (Pune)

Application Developer- Airflow / Astronomer Migration Job Location: Pune Location Flexibility: Primary Location Only Req Id: 10312 Posting Start Date: 7/28/26 At Fujitsu, we've been driven to create a sustainable world through innovation since 1935. Today, we lead in digital transformation globally with our 130,000 employees across 50 countries. We empower our diverse community to achieve greatness through career development and opportunities. Explore our internal positions and join us in shaping a brighter future. Thank you for being a part of Fujitsu. We look forward to growing together toward a brighter future. Job Title: Application developer Experience: 3 to 5 years Location / Shift: - Location: Pune, India / Remote / Hybrid as per project need - Working Mode: Full-time assignment Client working hours may apply - Role Summary: You will work as a Data Engineer Consultant . You will support the migration of orchestration workflows from Azure Data Factory (ADF) to Astronomer / Apache Airflow . You will design, build, test, and document data workflows. You will work closely with the Principal Data Engineer and the Data Engineering team. You will also suggest improvements for performance, cost, reliability, and maintainability. Primary Skills: Must Have - Apache Airflow / Astronomer - Airflow DAG design and development - Python and SQL - dbt - Snowflake - Azure Blob Storage - Data pipeline orchestration - Workflow testing and validation Secondary Skills: Good to Have - Azure Data Factory (ADF) - ADF to Airflow migration experience - Data pipeline modernization experience - Snowflake performance tuning - dbt model and flow optimization - Git / Azure DevOps - CI/CD for data pipelines Monitoring and alerting for data workflows - Key Responsibilities 1) Requirement Understanding - Understand existing ADF pipelines and orchestration flows. - Analyze current workflow schedules, triggers, parameters, and dependencies. - Understand ingestion steps, transformation logic, and downstream impact. - Work with the Principal Data Engineer and team to clarify open points. Identify risks, blockers, assumptions, and dependencies early. - 2) Solution Design - Design the migration approach from ADF to Astronomer / Airflow . - Convert existing orchestration logic into clean Airflow DAG design. - Define DAG structure, task dependencies, retry logic, and schedule patterns. - Design workflows that are easy to maintain and support. Suggest improvements instead of only doing one-to-one migration. - 3) Development / Implementation - Design and build DAGs in Apache Airflow / Astronomer . - Develop and adapt data pipelines as per migration requirement. - Modify existing ingestion steps in Astronomer where required. - Modify existing dbt flows and transformations when needed. - Use Python and SQL for workflow logic, validation, and automation. Follow coding standards and project guidelines. - 4) Integration / Configuration - Configure schedules and dependencies for Airflow DAGs. - Integrate Airflow workflows with dbt , Snowflake , and Azure Blob Storage . - Ensure dbt jobs are properly triggered and monitored through Airflow. - Validate integration between ingestion, transformation, and consumption layers. Configure workflow parameters, environment settings, and required connections. - 5) Testing & Validation - Perform unit testing for DAGs and workflow components. - Perform integration testing for end-to-end data workflows. - Validate migrated workflows against existing ADF output wherever applicable. - Check data accuracy, completeness, and processing status. - Fix defects and retest before production readiness. Prepare test evidence and validation notes. - 6) Performance Optimization - Review existing workflows and identify improvement areas. - Optimize Airflow DAG performance and execution time. - Improve reliability using proper retries, failure handling, and dependency management. - Suggest cost-efficient execution patterns. - Improve maintainability by creating reusable workflow components. Proactively recommend better design wherever useful. - 7) Security, Compliance & Governance - Follow client security and data handling guidelines. - Use secure connection and access patterns as per project standards. - Avoid hardcoding secrets, passwords, or sensitive values. - Ensure access and workflow configurations are controlled and traceable. Follow required governance process for data pipeline changes. - 8) Deployment & Release Management - Support deployment of Airflow / Astronomer workflows across environments. - Prepare deployment steps and release notes. - Support production readiness checks before go-live. - Coordinate with the Data Engineering team during release activities. - Validate workflows after deployment. Support rollback or quick fix approach if any deployment issue occurs. - 9) Production Support & RCA - Monitor workflow execution and identify .