3 - 8 Yrs exp - Python AWS Data Engineer

Job Description

Role Overview

We are seeking a hands-on Python AWS Data Engineer to design, develop, and maintain robust ETL pipelines and cloud-based data solutions.

The ideal candidate will have strong expertise in Python, Spark, SQL , and AWS services , with experience in building scalable data pipelines, implementing data transformations, and ensuring high-quality, maintainable code.

You will collaborate closely with data architects, analysts, and business stakeholders to enable data-driven decision-making while working in an Agile environment .

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Key Responsibilities

• Design, develop, and maintain ETL pipelines using Python, Spark , and AWS services.
  

• Build, test, debug, and document Python and Spark applications .
  

• Work with AWS services including S3, ECS, Lambda, Glue, DynamoDB, SQS, SNS, IAM, and Athena .
  

• Write and optimize SQL queries, joins, and stored procedures for relational databases.
  

• Implement unit tests and validation using Pytest or Unittest frameworks.
  

• Collaborate with DevOps teams to maintain CI/CD pipelines using Git, Jenkins/Bamboo .
  

• Ensure scalability, performance, and reliability of data pipelines.
  

• Participate in Agile ceremonies and contribute to sprint planning, code reviews, and retrospectives.
  

• Document solutions, data flows, and ETL transformations for knowledge sharing and compliance.
  

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Requirements

Required Skills & Experience

• 3–8 years of hands-on experience in Python, Spark, SQL , and ETL development.
  

• Strong experience with AWS cloud services and cloud-native data solutions.
  

• Proficiency in ETL architecture and pipeline design.
  

• Experience with unit testing frameworks like Pytest and Unittest.
  

• Solid understanding of RDBMS, SQL queries, joins, stored procedures .
  

• Exposure to CI/CD and build automation tools (Git, Jenkins/Bamboo).
  

• Familiarity with Bitbucket, GitHub, Jira, Splunk, PostgreSQL is a plus.
  

• Excellent verbal and written communication skills .
  

• Ability to work in Agile/Scrum environments.
  

• Investment Management domain knowledge is an added advantage.
  

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Benefits

Why Work With Us

Empowering innovators to build the future of digital enterprise.

• Work on high-impact data engineering projects using cutting-edge cloud technologies.
  

• Collaborative, growth-focused environment that values innovation and ownership .
  

• Competitive pay, hybrid work flexibility, and exposure to enterprise-scale data platforms .
  

Requirements
Key Responsibilities Design, develop, and maintain ETL pipelines using Python, Spark, and AWS services.

Build, test, debug, and document Python and Spark applications.

Work with AWS services including S3, ECS, Lambda, Glue, DynamoDB, SQS, SNS, IAM, and Athena.

Write and optimize SQL queries, joins, and stored procedures for relational databases.

Implement unit tests and validation using Pytest or Unittest frameworks.

Collaborate with DevOps teams to maintain CI/CD pipelines using Git, Jenkins/Bamboo.

Ensure scalability, performance, and reliability of data pipelines.

Participate in Agile ceremonies and contribute to sprint planning, code reviews, and retrospectives.

Document solutions, data flows, and ETL transformations for knowledge sharing and compliance.

Required Skills & Experience 3–8 years of hands-on experience in Python, Spark, SQL, and ETL development.

Strong experience with AWS cloud services and cloud-native data solutions.

Proficiency in ETL architecture and pipeline design.

Experience with unit testing frameworks like Pytest and Unittest.

Solid understanding of RDBMS, SQL queries, joins, stored procedures.

Exposure to CI/CD and build automation tools (Git, Jenkins/Bamboo).

Familiarity with Bitbucket, GitHub, Jira, Splunk, PostgreSQL is a plus.

Excellent verbal and written communication skills.

Ability to work in Agile/Scrum environments.

Investment Management domain knowledge is an added advantage.