Hadoop Spark

Job description

- Strong experience in programming languages such as Python, Java, or Scala for data manipulation and engineering tasks. - Expertise in SQL and NoSQL databases - Hands-on experience with big data technologies like Hadoop, Spark, Kafka, and Hive to handle large-scale data processing and real-time data streams. - In-depth knowledge of data warehousing solutions such as Amazon Redshift, Google BigQuery, and Snowflake for building and managing data warehouses. - Proficiency in designing, developing, and maintaining ETL (Extract, Transform, Load) processes using tools like Apache NiFi, Talend, or Informatica. - Familiarity with cloud platforms like AWS, Azure, or Google Cloud for deploying, managing, and scaling data infrastructure and services. - Strong understanding of data modeling concepts and techniques to create efficient and scalable data models. - Experience with version control systems such as Git for code management and collaboration. - Knowledge of data governance, data quality standards, and data security practices to ensure compliance and protection of sensitive information