- Design, develop, and maintain ETL/ELT pipelines using PySpark for batch and streaming data processing.
- Build and manage data lake and data warehouse solutions on AWS, including S3, Redshift, Glue, EMR, Athena, and Lake Formation.
- Develop and orchestrate workflows using AWS Step Functions, Apache Airflow, or AWS Glue Workflows.
- Optimize Spark jobs for performance, cost, and scalability.
- Ingest data from APIs, databases, flat files, and streaming platforms such as Kafka/Kinesis.
- Implement data quality checks, validation frameworks, monitoring, and alerting.
- Collaborate with data analysts, data scientists, and business stakeholders.
- Design and maintain data models for analytics use cases.
- Write clean, well-documented, and testable code following engineering best practices.
- Ensure data security, governance, and compliance.
- Troubleshoot and resolve production data pipeline issues.
📌 Immediate Hiring For Data Engineer With AWS Pyspark Experience (Bengaluru)
🏢 Tranzeal
📍 Bengaluru
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