Immediate Hiring For Data Engineer With AWS Pyspark Experience

Tranzeal; Bengaluru; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

Tranzeal in Bengaluru is seeking a Data Engineer to design, build, and maintain PySpark ETL/ELT pipelines for batch and streaming data processing. You will develop data lake and data warehouse solutions on AWS (S3, Redshift, Glue, EMR, Athena).

You will orchestrate workflows with Airflow or AWS Glue Workflows, optimize Spark jobs, ingest data from APIs, databases, flat files, and Kafka/Kinesis, implement data quality checks, ensure security and governance, and collaborate with analysts, data

Qualifications

• Experience designing and maintaining PySpark ETL/ELT pipelines for batch and streaming data.
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Responsibilities

• Design and implement PySpark ETL/ELT pipelines for batch and streaming data.
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Skills

PySpark

ETL/ELT pipelines

AWS

Spark optimization

Data modeling

Data security & governance

Collaboration with analysts/scientists

Testing & documentation

Monitoring & alerting

Tools

Apache Airflow

Kafka/Kinesis

AWS Glue

S3

Redshift

EMR

Athena

Lake Formation

SQL & data modeling tools

Job description

Key Responsibilities:

• 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.