Data Engineer - ETL/SQL (6-8 yrs)

Job Description :

- Data Pipeline Development : Design, develop, and maintain highly scalable and optimized ETL pipelines using PySpark on the Cloudera Data Platform, ensuring data integrity and accuracy.

- Data Ingestion : Implement and manage data ingestion processes from a variety of sources (e.g., relational databases, APIs, file systems) to the data lake or data warehouse on CDP.

- Data Transformation and Processing : Use PySpark to process, cleanse, and transform large datasets into meaningful formats that support analytical needs and business requirements.

- Performance Optimization : Conduct performance tuning of PySpark code and Cloudera components, optimizing resource utilization and reducing runtime of ETL processes.

- Data Quality and Validation : Implement data quality checks, monitoring, and validation routines to ensure data accuracy and reliability throughout the pipeline.

- Automation and Orchestration : Automate data workflows using tools like Apache Oozie, Airflow, or similar orchestration tools within the Cloudera ecosystem.

- Monitoring and Maintenance : Monitor pipeline performance, troubleshoot issues, and perform routine maintenance on the Cloudera Data Platform and associated data processes.

- Collaboration : Work closely with other data engineers, analysts, product managers, and other stakeholders to understand data requirements and support various data-driven initiatives.

- Documentation : Maintain thorough documentation of data engineering processes, code, and pipeline configurations.

Qualifications :

Education and Experience :

- Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.

- 3+ years of experience as a Data Engineer, with a strong focus on PySpark and the Cloudera Data Platform.

Technical Skills :

- PySpark : Advanced proficiency in PySpark, including working with RDDs, DataFrames, and optimization techniques.

- Cloudera Data Platform : Strong experience with Cloudera Data Platform (CDP) components, including Cloudera Manager, Hive, Impala, HDFS, and HBase.

- Data Warehousing : Knowledge of data warehousing concepts, ETL best practices, and experience with SQL-based tools (e.g., Hive, Impala).

- Big Data Technologies : Familiarity with Hadoop, Kafka, and other distributed computing tools.