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Engineer-Core Java
Engineer-Core JavaTEPHRA • Raleigh, NC, United States
Engineer-Core Java

Engineer-Core Java

TEPHRA • Raleigh, NC, United States
[job_card.variable_days_ago]
[job_preview.job_type]
  • [job_card.full_time]
[job_card.job_description]

Description : Java Nifi

Technical Skills :

Strong NiFi Expertise : Deep understanding of 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 : Knowledge of big data technologies like Kafka ( Event driven & streaming architecture)

Airflow - Workflow orchestration

Responsibilities :

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

#LI-SP3

#LI-VX1

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Java • Raleigh, NC, United States

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