Data Engineer-Chennai

Aelius Consultants Delhi; Chennai District; On-site; INR 600,000 - 900,000; Full time

Job summary

Data Engineer role focusing on maintaining, expanding, and optimizing our data warehouse, pipelines, and data products. Strong AWS, PySpark, Python, SQL, and data pipeline design expertise required. Collaboration with multiple teams is essential.

Key highlights include 1+ year in Data Engineering and hands-on experience with large-scale engagements, ETL/ELT pipelines, data lakes, warehousing, and streaming technologies.

Qualifications

• Minimum 1+ years in Data Engineering (PySpark, AWS mandatory).
• Hands-on experience with large-scale data engagements.
• Experience with ETL/ELT pipelines, data lakes, warehousing, and streaming technologies.

Responsibilities

• Maintain, expand, and optimize data warehouse and pipelines.
• Collaborate with business users, developers, architects, analysts, and data scientists to ensure data delivery.
• Hands-on work with Python, SQL, and Spark in AWS-based environments.

Skills

PySpark

Python

SQL

Data pipeline design

Airflow

CI/CD tools

Git

Jenkins

Spinnaker

Ansible

NoSQL databases

Kafka

Kinesis

DynamoDB

Spark Streaming

AWS services

Data warehouse

Data lakes

Tools

AWS services (S3, EC2, Athena, Redshift, Glue, EMR, Lambda, RDS, Kinesis, DynamoDB, QuickSight)

ETL/ELT pipelines

Kafka, Kinesis, Spark Streaming

Airflow

Job description

Hi,

Role: Data Engineer As a Data Engineer, you will be responsible for maintaining, expanding, and optimizing our data warehouse, pipelines, and data products. You will collaborate with business users, developers, architects, analysts, and data scientists to ensure optimal data delivery. This role requires strong technical expertise in AWS, PySpark, Python, SQL, and data pipeline design, with hands‑on experience in large‑scale engagements.Key Highlights:

• Minimum 1+ years in Data Engineering (PySpark, AWS mandatory)
• Strong experience with AWS services (S3, EC2, Athena, Redshift, Glue, EMR, Lambda, RDS, Kinesis, DynamoDB, QuickSight)
• Expertise in ETL/ELT pipelines, data lakes, warehousing, and streaming technologies (Kafka, Kinesis, Spark Streaming)
• Proficiency in Python, SQL, Scala, Shell scripting, and orchestration tools (Airflow)
• Exposure to CI/CD tools (Git, Jenkins, Spinnaker, Ansible) and NoSQL databases
• Insurance domain experience preferred