AWS Data Engineer

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

Job summary

Zorba Consulting in Pune, India is seeking an experienced AWS Data Engineer with 6+ years of data engineering expertise to design, build, and optimize scalable data pipelines on AWS. The ideal candidate will drive ETL/ELT development, data lake and data warehouse architectures, and support advanced analytics initiatives across the organization.

You will work with Spark/PySpark, Redshift and Athena, implement governance and quality controls, and collaborate with data scientists, analysts, and

Qualifications

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

Responsibilities

• Design, develop, and maintain scalable data pipelines on AWS.
• Ingest data from multiple sources via ETL/ELT processes.
• Develop and manage data lakes and data warehouses on AWS.
• Ensure data quality, reliability, and performance for analytics.
• Implement data transformation and integration using Spark or Glue.
• Collaborate with data scientists and analysts to deliver datasets.
• Optimize queries in Redshift, Athena, and other AWS data services.
• Monitor, troubleshoot, and optimize data pipelines.
• Automate data processes using Python and SQL.

Skills

AWS services

SQL

Python

ETL pipelines

Data warehousing

Apache Spark / PySpark

Airflow

CI/CD / DevOps

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.