Data Engineer - AWS

Responsibilities:
Design, develop, and maintain scalable data transformation pipelines using AWS services (Lambda, Step Functions) and Python.
Build and optimize data processing workflows using PySpark and Databricks.
Design and maintain complex data calculation and transformation engines.
Manage and process large-scale datasets efficiently.
Develop and support SQL databases, including PostgreSQL and MongoDB.
Collaborate closely with software engineering teams on solution design and implementation.
Participate in code reviews, architecture discussions, and software planning activities.
Contribute to automation, testing, deployment, and continuous improvement initiatives.
Requirements:
Experience: 5-8 Years.
Required Skills: Python, PySpark, Databricks, AWS Lambda, AWS Step Functions, SQL, PostgreSQL / MongoDB, Data Engineering, and Data Transformation
Experience with large-scale data processing.
CI/CD, automation, and testing frameworks.
Strong hands-on experience with AWS Data Engineering services.
Expertise in Python, PySpark, Databricks, and SQL.
Excellent problem-solving and analytical skills.
Strong communication, collaboration, and documentation skills.
Ability to work effectively in agile and cross-functional teams.
Certifications: AWS Certifications (Preferred but Optional).

Experience
5-8 yrs