Must Have Skills
Python
PySpark
Apache Spark
AWS Redshift
AWS Glue
AWS EMR
AWS S3
AWS Lambda
SQL Development & Query Optimization
Data Warehousing (Redshift or Hive)
ETL/ELT Pipeline Development
Airflow (or similar scheduling tools)
Hadoop Ecosystem
Data Pipeline Development (Batch & Near Real-Time)
Data Security & Data Protection
OLTP and OLAP Database Concepts

Positive to Have Skills
Data Lakes
Data Modeling
Netezza
Informatica
DynamoDB
MongoDB
AWS Athena
AWS Step Functions
Investment Banking Domain
NoSQL Databases

Responsibilities
Design, develop, and maintain scalable data pipelines using AWS services and PySpark.
Create and maintain optimal data pipeline architecture for effective data processing.
Build data ingestion, transformation,



and ETL workflows.
Develop batch and near real-time data processing solutions.
Work with large and complex datasets to meet business requirements.
Manage and optimize data warehouses using AWS Redshift or Hive.
Ensure data quality, integrity, security, and governance standards.
Perform SQL tuning and performance optimization.
Automate data workflows and improve platform scalability.
Collaborate with Product, Data, Engineering, and Business teams for solution delivery.
Create technical documentation and support operational readiness.

📌 Senior Aws Data Engineer Pune/ Bangalore/mumbai/chennai
🏢 Tata Consultancy Services
📍 Pune