Data Engineer

We are looking for a Data Engineer who understands how data works beyond writing code. This role requires hands-on experience in Python and SQL, strong analytical judgment, and the ability to understand data logic from source to consumption.

You will design, build, and maintain data pipelines that support analytics, machine learning, and data-driven decision-making in a pharmaceutical-related environment. The role works closely with AI, Data, Product, and Machine Learning teams, so experience or interest in Generative AI will be an advantage.

What You'll Do

• Design, develop, and maintain ETL/ELT pipelines to extract, transform, and load data from multiple sources into data lakes and data warehouses.
• Build data transformation logic and develop data models to support analytics and machine learning workflows.
• Collaborate with Product Analysts, Data Scientists, and ML Engineers to ensure data is accurate, accessible, and ready for use.
• Maintain data quality controls, data catalogs, orchestration, logging, and monitoring processes.
• Apply test-driven development practices to improve the reliability of data solutions.
• Contribute to information architecture and follow version control best practices using Git.
• Use Generative AI tools where relevant and continue developing AI-enabled data engineering practices.

What We're Looking For

• Strong experience with Databricks and AWS services such as S3, IAM, Redshift, Glue, Lambda, Step Functions, and CloudWatch.
• Hands-on experience with ETL/ELT development and workflow orchestration.
• Strong proficiency in Python and SQL.
• Experience with GitHub and CI/CD pipelines, especially GitHub Actions.
• Familiarity with GenAI-powered development tools such as GitHub Copilot or similar tools is a plus.
• Good communication skills with the ability to document technical processes clearly.
• Ability to understand business context, data structure, and technical requirements, and turn them into practical data solutions.

Benefits & Welfare

• Provident Fund to support long-term financial planning.
• Group health insurance for employees.
• Hybrid working arrangement with Work From Home options.
• Financial support and employee assistance benefits in various cases.
• Transportation expense reimbursement when traveling to client offices for work-related purposes.
• Office pantry including coffee, Ovaltine, instant noodles, and other refreshments.
• Opportunity to work with modern data, AI, and cloud technologies in real business use cases.