DEX Engineer
Responsibilities:
• Build and optimize large-scale data pipelines using Python and Apache Spark to support reliable data processing.
• Develop ETL workflows that collect, transform, and deliver data from multiple source systems into analytical platforms.
• Work with Hadoop-based environments to manage distributed data processing and storage effectively.
• Implement and support Kafka-driven streaming solutions for near real-time data ingestion and integration.
• Monitor pipeline performance, troubleshoot data issues, and improve processing efficiency across engineering workflows.
• Collaborate with technical teams to understand data needs and translate them into scalable engineering solutions.
• Maintain data quality standards by validating outputs, resolving inconsistencies, and supporting dependable data availability.
• Contribute to ongoing enhancements of data architecture, including updates to existing platforms and operational processes.
Qualifications:
• Hands-on experience with Apache Spark for large-volume data processing.• Strong programming ability in Python for data engineering and automation tasks.
• Working knowledge of Apache Hadoop and distributed data ecosystems.
• Experience using Apache Kafka for event-driven or streaming data solutions.
• Proven background in ETL design, development, and support.
• Ability to troubleshoot data pipeline issues and improve performance in complex environments.
• Strong collaboration and communication skills in cross-functional technical settings.
Compensation
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