Data Engineer; Pyspark

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.

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.

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

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

Implement data quality checks, monitoring, and validation routines to ensure data accuracy and reliability throughout the pipeline.

Automate data workflows using tools like Apache Oozie, Airflow, or similar orchestration tools within the Cloudera ecosystem.

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

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

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

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

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

PySpark:
Advanced proficiency in PySpark, including working with RDDs, Data Frames, 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.

Orchestration and Scheduling:
Experience with Apache Oozie, Airflow, or similar orchestration frameworks.

Scripting and Automation:
Strong scripting skills in Linux.

Strong analytical and problem-solving skills.

Excellent verbal and written communication abilities.

Ability to work independently and collaboratively in a team environment.

Attention to detail and commitment to data quality.

• Be part of a dynamic team exposed to cutting-edge technologies in big data and machine learning.
• Work on impactful projects that bring high-quality traffic to eBay and improve product purchase conversions.
• Collaborate with global teams and contribute to innovative platforms that accelerate marketing efficiency.