Aws Data Engineer

Symbiosis Management Consultants; Coimbatore District; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Symbiosis Management Consultants in Coimbatore invites an experienced AWS Data Engineer to design and build scalable cloud-based data solutions on AWS. The role requires 5-8 years of experience and BE/B.Tech or ME/M.Tech, with work undertaken from the office in Coimbatore.

You will design, develop, and optimize AWS data pipelines, build ETL/ELT workflows, and develop data lakes and data warehouses. Focus on data quality, security and performance while collaborating with cross-functional teams.

Qualifications

• BE/B.Tech / ME/M.Tech is required.
• 5-8 years of experience in data engineering or AWS-based data platforms.

Responsibilities

• Design, develop, and optimize scalable AWS data pipelines.
• Build and maintain ETL/ELT workflows for large-scale data processing.
• Develop data lakes and data warehouses on AWS.
• Ensure data quality, security, governance, and performance optimization.
• Collaborate with cross-functional teams to deliver reliable data solutions.

Skills

AWS Glue

S3

Redshift

Athena

EMR

Lambda

ETL/ELT Development

Data Pipelines

Python

Java

SQL

PySpark

Apache Spark

Kafka

Hadoop

MongoDB

Amazon RDS

Time-Series Databases

Data Lakes

Data Warehousing

Data Modeling

AWS Cloud Services

Performance Optimization

Education

BE/B.Tech

ME/M.Tech

Job description

AWS Data Engineer

Location: Coimbatore (Work From Office)
Qualification: BE/B.Tech / ME/M.Tech
Experience: 5-8 Years

We are looking for an experienced AWS Data Engineer with strong expertise in designing and building scalable cloud-based data solutions on AWS.

Key Skills:

• AWS Glue, S3, Redshift, Athena, EMR, Lambda
• ETL/ELT Development & Data Pipelines
• Python, Java, SQL, PySpark
• Apache Spark, Kafka, Hadoop
• MongoDB, Amazon RDS, Time-Series Databases
• Data Lakes, Data Warehousing & Data Modeling
• AWS Cloud Services & Performance Optimization

Role Responsibilities:

• Design, develop, and optimize scalable AWS data pipelines.
• Build and maintain ETL/ELT workflows for large-scale data processing.
• Develop data lakes and data warehouses on AWS.
• Ensure data quality, security, governance, and performance optimization.
• Collaborate with cross-functional teams to deliver reliable data solutions.