Airflow Developer

Job Summary:

We are seeking a skilled Airflow Developer with 4-5 years of experience to design, implement, and maintain efficient, scalable, and reliable workflows using Apache Airflow. The ideal candidate will have a strong understanding of data pipelines, ETL processes, and orchestration techniques. You will collaborate with cross-functional teams to ensure seamless integration and optimization of workflows in our data ecosystem.

Key Responsibilities:

  • Design and develop workflows, DAGs (Directed Acyclic Graphs), and custom operators using Apache Airflow.
  • Collaborate with data engineers, analysts, and stakeholders to understand requirements and translate them into scalable workflows.
  • Monitor, troubleshoot, and optimize Airflow pipelines to ensure reliability and performance.
  • Integrate Airflow with various data sources, storage systems, and APIs.
  • Implement best practices for code quality, version control, and deployment processes.
  • Write clear documentation for workflows, configurations, and processes.
  • Ensure data pipeline scalability, security, and maintainability by implementing appropriate solutions.
  • Manage and maintain the Airflow environment, including upgrades and plugin configurations.

Required Skills and Qualifications:

  • 4–5 years of experience in building and managing workflows with Apache Airflow.
  • Proficiency in Python programming for Airflow DAGs and custom operator development.
  • Strong understanding of ETL/ELT processes and data pipeline orchestration.
  • Experience working with SQL and databases (e.g., PostgreSQL, MySQL, or NoSQL).
  • Familiarity with cloud platforms (AWS, GCP, or Azure) and their data services.
  • Knowledge of CI/CD pipelines and version control systems (e.g., Git).
  • Strong problem-solving skills and attention to detail.


Preferred Qualifications:

  • Experience with containerization tools like Docker and orchestration systems like Kubernetes.
  • Familiarity with big data technologies such as Spark, Hadoop, or Kafka.
  • Understanding of data warehousing solutions like Snowflake, Redshift, or BigQuery.
  • Knowledge of monitoring and alerting tools (e.g., Prometheus, Grafana).


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