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Data Engineer – PySpark | SQL | AWS
Tranzeal Inc.
🇮🇳 India
Hybrid
4 weeks ago
- PySpark
- SQL
- AWS
- Machine Learning
- ETL
- ELT
- Redshift
- EMR
- Athena
- Step Functions
- Apache Airflow
- AWS Glue
- Kinesis
4 weeks ago
- Role: Data Engineer
- Positions: 2
- Location: Bengaluru
- Work Mode: Hybrid
- Max CTC: 24 LPA
- Key Skills: PySpark, SQL, AWS
- End Client Name: Intuit
Job Description:
We're looking for skilled Data Engineers to design, build, and maintain scalable data pipelines supporting analytics, reporting, and machine learning initiatives. The role requires strong experience with PySpark, SQL, and the AWS ecosystem.
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.
Data Engineer – PySpark | SQL | AWS · Tranzeal Inc.