The Role
Design, develop, optimize, and deploy high-performance data processing applications using Scala and Apache Spark on Cloudera CDH. Build and tune ETL pipelines integrating HDFS, Hive, Impala, HBase, and Kafka. Ensure data integrity and security, troubleshoot performance, collaborate with data scientists and analysts, and implement version control and CI/CD.
Summary Generated by Built In
Key Responsibilities:
- 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.
Required Skills & Experience:
- Minimum 8 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).
Compensation, Benefits and Duration
Minimum Compensation: USD 46,000
Maximum Compensation: USD 161,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
Skills Required
- Minimum 8 years of experience in application development
- Hands-on experience with Apache Spark, Scala, and Spark SQL
- Experience with Cloudera Hadoop (CDH) components such as HDFS, Hive, Impala, HBase, Kafka, and Sqoop
- Familiarity with Big Data technologies including Flume, Oozie, and Nifi
- Experience building and optimizing ETL pipelines using Spark 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
- Familiarity with CI/CD tools (e.g., Jenkins, GitLab) and implementing CI/CD for Spark applications
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The Company