Apache Airflow (MWAA)
Experience Level: 6 to 10 Years
Key Responsibilities
Workflow Design & Development: Build, deploy, and optimize DAGs (Directed Acyclic Graphs) on AWS MWAA to orchestrate data pipelines, ETL processes, and automation tasks.
Workflow Orchestration: Implement scheduling, monitoring, troubleshooting, and performance tuning for Airflow jobs running in MWAA.
AWS Resource Integration: Leverage AWS services including S3, Redshift, EMR, Lambda, Glue, and RDS within Airflow workflows.
Automation: Design and implement CI/CD pipelines for seamless deployment and updates of Airflow DAGs and plugins.
Monitoring & Logging: Configure and maintain integration with Amazon CloudWatch for monitoring workflow execution, logging, and alerting.
Security & Compliance: Use IAM roles and VPCs to enable secure access and networking for Airflow tasks, ensuring compliance with data governance policies.
Documentation & Collaboration: Create clear documentation and collaborate with analytics, engineering, and business teams to deliver high-quality data solutions.
Maintenance & Upgrades: Manage Airflow environment upgrades, scalability, and patching in MWAA.
Required Skills & Qualifications
Experience: 4 to 10 years in data engineering or related field, with direct experience managing Airflow pipelines, preferably on AWS MWAA.
Programming Languages: Strong proficiency in Python (Airflow DAGs), SQL, and scripting for data tasks.
AWS Services: Hands-on expertise with AWS data and storage services (S3, Lambda, EMR, Glue, Redshift, RDS).
DevOps: Familiarity with CI/CD tools, version control (Git), and infrastructure as code practices is a plus.
Security: Understanding of IAM, VPC, networking, and data security best practices in AWS.
Problem Solving: Excellent debugging, troubleshooting, and analytical skills for distributed workflows.
Communication: Clear and effective communicator, able to convey technical concepts to cross-functional teams.
Preferred Skills
Experience with big data frameworks (Spark, Hadoop)
Exposure to containerization technologies (Docker, Kubernetes)
Familiarity with other orchestration tools (Luigi, Prefect)
Experience in cloud migration and workflow optimization
Education
Bachelors or Masters degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent experience.
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