AWS Data Engineer

Zorba Consulting; Chennai District; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Zorba Consulting is seeking an experienced AWS Data Engineer to design scalable data pipelines on AWS. The role requires building ETL/ELT processes, data lakes, and data warehouses to support analytics initiatives in Chennai. Proficiency in SQL, Python, and Spark is essential.

The candidate will work with AWS services such as S3, Glue, Redshift, Lambda, EMR, Athena, and orchestration via Airflow. Strong data modeling and DevOps practices are required to ensure data quality and performance.

Qualifications

• 6+ years of experience in Data Engineering or Big Data development.
• Strong experience with AWS services including S3, Glue, Redshift, Lambda, EMR, Athena, Step Functions.
• Proficient SQL and Python programming.
• Experience building ETL pipelines and data workflows.
• Knowledge of data warehousing and big data concepts.
• Familiarity with Spark/PySpark.
• Experience with workflow orchestration tools like Airflow.
• Understanding of CI/CD and DevOps practices.

Responsibilities

• Design, develop, and maintain scalable data pipelines using AWS services.
• Build and optimize ETL/ELT processes to ingest data from multiple sources.
• Develop and manage data lakes and data warehouses on AWS.
• Work with large-scale datasets ensuring data quality and performance.
• Implement data transformation and integration using AWS Glue or Spark.
• Collaborate with data scientists, analysts, and business teams to deliver data.
• Optimize queries and performance in Redshift, Athena, or other AWS data services.
• Ensure data governance, security, and compliance standards.
• Monitor and troubleshoot data pipelines and workflows.
• Automate data processes using Python, SQL, and scripting tools.

Skills

AWS services

SQL

Python

ETL pipelines

Data modeling

Spark / PySpark

Airflow

CI/CD / DevOps

Tools

Apache Spark

Airflow

Job description

We are seeking an experienced AWS Data Engineer with 3+ years of experience in building scalable data pipelines, designing data architectures, and working with cloud-based data platforms.

The ideal candidate will have strong expertise in AWS services, ETL development, data warehousing, and big data technologies to support advanced analytics and business intelligence initiatives.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using AWS cloud services.
• Build and optimize ETL/ELT processes to ingest data from multiple sources.
• Develop and manage data lakes and data warehouses on AWS.
• Work with large-scale datasets and ensure data quality, reliability, and performance.
• Implement data transformation and integration solutions using tools such as AWS Glue or Apache Spark.
• Collaborate with data scientists, analysts, and business teams to deliver high-quality datasets.
• Optimize queries and improve performance in Amazon Redshift, Athena, or other AWS data services.
• Implement data governance, security, and compliance standards.
• Monitor and troubleshoot data pipelines and workflows.
• Automate data processes using Python, SQL, and scripting tools.

Required Skills

• 6+ years of experience in Data Engineering or Big Data development.
• Strong experience with AWS services, such as Amazon S3, AWS Glue, Amazon Redshift, AWS Lambda, Amazon EMR, Amazon Athena, AWS Step Functions.
• Strong SQL and Python programming skills.
• Experience building ETL pipelines and data workflows.
• Knowledge of data modeling, data warehousing, and big data concepts.
• Experience with Apache Spark / PySpark.
• Familiarity with workflow orchestration tools like Apache Airflow.
• Understanding of CI/CD and DevOps practices.