Design, build, and maintain scalable data pipelines and warehouse models for life science analytics at a US-based health-tech company. Fully remote role aligned to US Eastern hours.

About the Company

IntegriChain is the data and application backbone for market access departments of Life Sciences manufacturers. Over 250 manufacturers rely on the ICyte Platform to orchestrate commercial and government payer contracting, patient services, and distribution channels. ICyte unites financial, operational, and commercial datasets to support therapy access in the era of specialty and precision medicine, freeing customers to focus on data-driven decisions rather than manual processes. Headquartered in Philadelphia, PA (USA), IntegriChain has offices in Pune, India and Medellín, Colombia, and offers a hybrid working environment with periodic team workshops and occasional international travel.

Role Overview

We are seeking a Data Engineer to join our team in India. This is a fully remote role with working hours aligned to US Eastern Time (approximately 6:30 PM to 2:30 AM IST during US Daylight Saving Time and 7:30 PM to 3:30 AM IST otherwise). The mission of the Data Engineer is to design, build, and maintain scalable, reliable data pipelines and warehouse models that turn complex life science and healthcare data into clean, trusted datasets that power analytics and decision-making. You will work closely with data analysts, data scientists, and fellow engineers to ensure data accuracy, consistency, and timeliness.

Key Responsibilities

• Develop scalable, reliable, and efficient data pipelines using dbt, Python, or other ELT tools.
• Design, implement, and maintain scalable data orchestration and transformation processes.
• Build and maintain complex dbt models with testing and documentation.
• Develop data warehouse structures including dimension and fact tables.
• Implement Type 1 and Type 2 slowly changing dimensions (SCDs) to capture historical and current data accurately.
• Manage and execute data mart updates to support downstream reporting and analytics.
• Build conformed dimensions through integration with Master Data Management (MDM) systems.
• Work with life science and healthcare datasets, applying domain knowledge to ensure data quality and relevance.
• Collaborate with cross-functional teams to understand data requirements and translate them into technical solutions.
• Partner with data analysts and data scientists to deliver clean, well-structured datasets for analysis and modeling.
• Collaborate with fellow engineers across Git repositories, following sound version control and code review practices.

Tech Stack

• Data Transformation & Orchestration: dbt (core/preferred), Python, ELT tools, SSIS, PowerCenter
• Data Warehouse: Snowflake (preferred), dimensional modeling (star schema), Type 1/Type 2 SCDs, data marts, MDM integration
• Cloud Platforms: Azure or AWS
• Version Control: Git
• Certifications (preferred): Snowflake or dbt certifications
• Domain: Life science/healthcare data quality and compliance considerations

Bachelor's degree in CS or equivalent; advanced SQL; strong data warehouse and dimensional modeling skills; hands-on with dbt, Python, ETL tools (SSIS, PowerCenter); Git experience; life science/healthcare data experience preferred; Snowflake and cloud platform (Azure/AWS) knowledge.

Mission-driven work improving patients' lives; excellent medical benefits; flexible PTO; 700+ free development courses.