Senior Big Data Developer - $130-150k - Hybrid - Pheonix AZ, New York, Fort Lauderdale. Role Overview: We are seeking a skilled Senior Big Data Developer to join our team. The ideal candidate will bring extensive experience in big data processing and analysis, with at least 3 years of hands-on expertise in Apache Spark. You will be responsible for designing, implementing, and optimizing data pipelines and applications that handle large-scale data in real-time and batch processing environments. Key Responsibilities: Data Pipeline Development: Design, develop, and maintain large-scale, distributed data pipelines using Apache Spark. Performance Optimization: Implement best practices for optimizing Spark jobs for performance and scalability. Integration: Work with diverse data sources, including HDFS, NoSQL databases, relational databases, and cloud storage. Collaboration: Partner with data scientists, analysts, and stakeholders to understand requirements and deliver data solutions. Real-time Processing: Develop real-time data streaming applications using Spark Streaming or similar technologies. Code Quality: Write clean, maintainable, and reusable code, following best practices for version control, testing, and documentation. Troubleshooting: Identify and resolve issues in Spark jobs and data pipelines. Required Skills and Qualifications: Experience: 8 to 12 years in software development, with a focus on big data solutions. 3 years of hands-on experience in Apache Spark (batch and streaming). Technical Skills: Proficient in programming languages such as Scala, Python, or Java. Strong understanding of distributed computing principles. Experience with big data ecosystems (Hadoop, HDFS, Hive, Kafka). Familiarity with cloud platforms like AWS, Azure, or GCP. Proficient in SQL and experience with relational databases. Tools and Frameworks: Version control systems (Git, GitHub, Bitbucket). CI/CD pipelines and DevOps practices. Soft Skills: Excellent problem-solving and analytical skills. Strong communication and teamwork abilities. Others: Knowledge of machine learning frameworks and integration with Spark (e.g., MLlib). Experience with containerization and orchestration tools (Docker, Kubernetes). Certifications in Big Data or Cloud technologies. Experience in developing solutions for Payment Networks and Payment or Financial transaction processing.
