Java Developer ( Nifi, Airflow)

Title: Java Developer ( Nifi, Airflow)
Location: Phoenix, AZ / Raleigh, NC OR Remote
Duration: 12 months+

Pay Rate: $56/hr on C2C
Only visa independent (USC, GC, GC-EAD, H4-RAD & L2-EAD)

Description:
• Strong NiFi Expertise: Deep understanding of Apache NiFi architecture, processors, controllers, and data flow management capabilities.
• Programming Languages: Proficiency in Java, Spring boot & API Microservices.
• Database and SQL: Familiarity with databases, SQL, and data manipulation techniques.
• Big Data Technologies: Kafka (Event-driven & streaming architecture)
• Apachae Airflow – Workflow orchestration.
• Design and Implementation: Creating and implementing data flow solutions using NiFi, including defining data sources, destinations, and transformation processes.
• Ingestion and Transformation: Managing data ingestion from various sources (e.g., files, databases, APIs) and transforming data into desired formats for downstream consumption.
• Routing and Enrichment: Configuring NiFi to route data to appropriate destinations and enriching data with additional information (e.g., timestamps, location).
• Scalability and Performance: Ensuring data flows are scalable and performant to handle varying data volumes and velocity.
• NiFi Cluster Management: Maintaining and improving NiFi clusters, including configuration, optimization, and troubleshooting.
• Microservices Integration: Developing and integrating microservices to support data conditioning, format validation, and transformation processes.
• Troubleshooting and Issue Resolution: Identifying and resolving issues related to data flows, NiFi configurations, and data integration processes
• Airflow Expertise: Possessing deep knowledge of Airflow’s architecture, including schedulers, executors (Celery, Kubernetes), and plugin development.
• Workflow Design and Development: Designing and developing complex, modular, and reusable DAGs (Directed Acyclic Graphs) to automate data pipelines.
• Performance Optimization: Identifying and addressing performance bottlenecks in Airflow environments and implementing best practices for orchestration and scheduling.