Data Engineering Analyst

Overview

Data Engineering Analyst to build and optimize cloud-based data and AI solutions, enabling analytics, automation, and AI-driven capabilities.

What you'll do

• Develop, enhance, and maintain cloud-based data solutions and pipelines.
• Assist with implementing AI and data platform capabilities under senior engineers.
• Design and optimize ETL/ELT workflows and data processing solutions.
• Troubleshoot, monitor, and improve platform reliability and performance.
• Collaborate with product owners, business stakeholders, and engineering teams to deliver solutions.
• Participate in code reviews, testing, and deployment processes.
• Support implementation of secure, scalable, and well-governed cloud solutions.

What you'll need

• 2-5 years of experience in software engineering and data engineering.
• Experience working with cloud platforms, preferably AWS.
• Familiarity with AWS services such as S3, Lambda, IAM, API Gateway, or similar.
• Exposure to Infrastructure-as-Code tools such as Terraform or CloudFormation.
• Experience with data engineering technologies such as AWS Glue, Spark, Databricks, or equivalent.
• Proficiency in SQL for data analysis and transformation.
• Working knowledge of Python for automation and data processing.
• Familiarity with source control and CI/CD using tools such as GitHub Actions, Jenkins, or GitLab CI.
• Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Technology, or related field.

Details

• Exposure to GenAI platforms (e.g., AWS Bedrock, Azure AI) is a plus.
• Desirable: understanding Agile methodologies.
• Desirable: exposure to Jira or similar project management tools.
• Advantage: experience working with global teams or healthcare/insurance domains.