Summary
Confidential company is seeking a Data Engineer to support secure, reliable, and scalable data platforms and pipelines. The role focuses on developing ETL/ELT pipelines, automating data ingestion, optimizing PySpark processing, orchestrating workflows, and supporting analytics, reporting, AI/ML, and business operations.
Responsibilities
- Data Pipeline Development, Enhancement & Maintenance
- Design, build, and maintain scalable ETL/ELT pipelines
- Automate data ingestion from multiple data sources
- Ensure reliable, high-performance, and scalable data movement
- Develop and Eligible to workimize PySpark-based data processing frameworks
- Build and manage Airflow workflows and orchestration pipelines
- Work with Hive and Kafka-based batch and streaming data solutions
- Implement data quality, monitoring, governance, and operational controls
- Support production incidents, performance tuning, and continuous improvement initiatives
- The Data Engineer will be responsible for designing, building, governing, and Eligible to workimizing data platforms, pipelines, and integrations to ensure secure, reliable, and scalable data availability for analytics, reporting, AI/ML, and business operations
Skills
- Google Cloud Platform
- PySpark
- Python
- Airflow
- Hive
- Kafka
Qualifications
Must Haves
- Google Cloud Platform
- PySpark
- Python
- Airflow
- Hive
- Kafka