Big Data Developer
Procal Technologies
Bernards, NJ, United States
6 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source
Tech stack
Java (Programming Language)
Artificial Intelligence
Apache HTTP Server
Big Data
Computer Programming
Databases
Data Integration
Data Security
Linux
Distributed Data Store
MapReduce
Python (Programming Language)
+16 more
Performance Tuning
Scala (Programming Language)
SQL Databases
Data Streaming
Web Services
Data Processing
Caching
Data Lakes
Integration Tests
Optimization Algorithms
Apache Kafka
Free and Open-Source Software
Video Streaming
Stream Processing
Data Pipelines
Service Stack
Job description
Find out more about the daily tasks, overall responsibilities, and required experience for this opportunity by scrolling down now.
- Design and lead end-to-end data integration
- Perform performance tuning, diagnose, and resolve complex big data and streaming technical issues.
- Design and implement scalable solutions across the technology stack, including data processing, database, web services, network, and security layers.
- Perform integration testing and provide support to QA teams on large-scale projects.
- Contribute to requirements analysis, project estimation, system design, coding, and testing.
- Evaluate and implement appropriate third-party libraries and software to enhance product capabilities.
- Stay current with emerging techniques and trends in big data and AI/ML.
Requirements
- 5+ years of hands-on experience designing and implementing data applications in production using Java, Python, or Scala on big data platforms, with deep expertise in big data technologies and data optimization techniques.
- 5+ years of hands-on experience with streaming technologies, specifically with a strong focus on Kafka, and various open-source software platforms (e.g., Apache ecosystem, Linux).
- Proven ability to optimize data flow and design efficient, scalable data pipelines, including data lakes and warehouses on containerized clusters.
- Strong understanding of distributed data architecture concepts (e.g., caching, MapReduce, stream processing).
- Solid knowledge of data security, governance, and compliance.
- Proficiency in programming languages: Java, Python, Scala, and SQL.
- Strong analytical capabilities, creativity, and critical thinking skills. xrbllit
- Effective written and verbal communication, with the ability to facilitate team collaboration.
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