Day To Day Responsibilities:

• Design, develop, and optimize Hadoop-based applications for large-scale data processing.
• Implement data warehouse solutions and ensure efficient data storage and retrieval.
• Work with ETL processes to integrate data from various sources.
• Develop and optimize Spark applications for real-time and batch processing.
• Ensure data quality, governance, and security in compliance with industry best practices.
• Collaborate with cross-functional teams in an Agile development environment.
• Troubleshoot performance issues and optimize Hadoop cluster performance.
• Work with banking and financial data to ensure compliance with regulatory requirements (if applicable).

Required Skills:

• 7+ years of experience in Hadoop development.
• Strong knowledge of Hadoop ecosystem (HDFS, MapReduce, YARN, Hive, HBase, Impala).
• Experience in data warehousing and data modeling concepts.
• Hands-on experience with ETL tools and data integration frameworks.
• Proficiency in Apache Spark for large-scale data processing.
• Experience with Agile methodologies and DevOps practices.
• Strong expertise in SQL and NoSQL databases.
• Good knowledge of Python, Scala, or Java for big data processing.
• Familiarity with cloud platforms (AWS, Azure, or GCP) for Hadoop-based solutions.
  
  Pay rate Range: $60/HR-$65/HR