AWS Data Engineers to be part of our Data & Analytics practice and contribute to large-scale cloud data engineering initiatives.
Location
Bangalore | Hyderabad | Chennai
Experience
8 to 12 Years
Key Skills
Python
PySpark
AWS S3, EMR, Glue, Lambda, IAM, Athena, Redshift
SQL & Data Warehousing Concepts
ETL / ELT Development
Data Lake & Data Warehouse Architecture
Git / GitHub
Spark Performance Optimization
Preferred Skills
Databricks
Apache Airflow
dbt
Snowflake
Kafka
Terraform
CI/CD Pipelines
Docker / Kubernetes Role Overview The role involves designing, developing, and optimizing scalable data pipelines and cloud-native data solutions on AWS. The ideal candidate should have solid hands-on experience in Python, PySpark, AWS data services, ETL/ELT frameworks, and large-scale data processing settings.
Responsibilities
Design and develop scalable data pipelines using Python and PySpark.
Build and optimize ETL/ELT processes on AWS cloud platforms.
Create and maintain Data Lake and Data Warehouse solutions.
Develop batch and real-time data processing applications.
Perform data quality validation, monitoring, and troubleshooting.
Optimize Spark workloads for performance, scalability, and cost efficiency.
Collaborate with stakeholders, architects, and development teams to deliver enterprise-scale data solutions.
Support production deployments and critical incident resolution.
Qualification:
BE / B.Tech / MCA / M.Tech or equivalent.
If you are interested, please share your updated CV.