Data Architect

Role Overview

Key Responsibilities:

• Architect and design large-scale, distributed big data solutions using Java and big data technologies to handle high-volume data processing and analytics.
• Develop, test, and deploy data processing applications using Apache Spark and Scala.
• Optimize and tune Spark applications for better performance on large-scale data sets.
• Work with the Cloudera Hadoop ecosystem (e.g., HDFS, Hive, Impala, HBase, Kafka) to build data pipelines and storage solutions.
• Collaborate with data scientists, business analysts, and other developers to understand data requirements and deliver solutions.
• Design and implement high-performance data processing and analytics solutions.
• Ensure data integrity, accuracy, and security across all processing tasks.
• Troubleshoot and resolve performance issues in Spark, Cloudera, and related technologies.
• Implement version control and CI/CD pipelines for Spark applications.

• Minimum 15+ years of experience in application development.
• Strong hands on experience in Apache Spark, Scala, and Spark SQL for distributed data processing.
• Hands-on experience with Cloudera Hadoop (CDH) components such as HDFS, Hive, Impala, HBase, Kafka, and Sqoop.
• Familiarity with other Big Data technologies, including Apache Kafka, Flume, Oozie, and Nifi.
• Experience building and optimizing ETL pipelines using Spark and working with structured and unstructured data.
• Experience with SQL and NoSQL databases such as HBase, Hive, and PostgreSQL.
• Knowledge of data warehousing concepts, dimensional modeling, and data lakes.
• Ability to troubleshoot and optimize Spark and Cloudera platform performance.
• Familiarity with version control tools like Git and CI/CD tools (e.g., Jenkins, GitLab).