Data Engineer

!! Experience in Pharma/Healthcare is mandatory for this role - Immediate joiners preferred !!

About PharmSight

PharmSight is a rapidly growing strategic consulting firm dedicated to advancing bio-pharmaceutical innovation. We deliver bespoke solutions that address critical business challenges, with a focus on competitive intelligence, forecasting, launch strategy, and marketing analytics. As we continue to expand our advanced analytics and data engineering capabilities, we are seeking a Data Engineer (4–8 years) to support the development of next-generation commercial data platforms for global pharma clients.

Why join PharmSight?

• Competitive Compensation: Best-in-class salary with structured career progression
• Flexible Work Environment: Option to work from anywhere, at any time
• Global Client Exposure: Collaborate with leading pharmaceutical companies on impactful projects
• Career Growth & Recognition: A flat hierarchy with ample opportunities for leadership and professional development

Role Overview

As a Data Engineer, you will play a key role in building scalable commercial data and analytics platforms that streamline operations and enable advanced analytics and AI use cases. This role is suited for hands-on engineers who thrive in high-ownership environments and enjoy designing modern, cloud-native data solutions.

Key Responsibilities

• Build Scalable Data Platforms: Design and develop high-performance ELT pipelines ingesting CRM, sales, claims, and commercial datasets into modern cloud data warehouses
• Architect Analytics-Ready Models: Develop dimensional models (star/snowflake schemas) to support KPI frameworks and advanced analytics use cases
• Drive Cloud-Native Engineering: Build and optimize data platforms on AWS/Azure/GCP using tools such as Snowflake (should be experienced in dbt Orchestration Components, Tasks, Snowpark, Cortex AI, Intelligence, Fivetran / CDC tools), Redshift, BigQuery, Spark, Airflow.
• Ensure Data Reliability: Implement automated testing, monitoring, and data quality frameworks to enable trusted analytics at scale
• Optimize for Performance & Scale: Tune queries, optimize compute costs, data warehouse performance using clustering, query tuning and design scalable workflows to support high-volume commercial datasets
• Design and Automate: Develop End-to-end ELT pipelines orchestration frameworks, ensuring data quality, idempotency, and fault tolerance across workflows.

Requirements

• Experience: 4–8 years of experience in Data Engineering or Analytics
• Programming & Querying: Strong Python skills and advanced SQL proficiency
• Data Engineering Stack: Hands-on experience with Spark, Airflow, dbt (preferred), Snowflake (mandatory) and Databricks (good to have)
• Cloud Platforms: Experience building and managing data pipelines on AWS, Azure, or GCP
• Engineering Practices: Familiarity with CI/CD pipelines, Docker, and Git-based workflows
• Build and deploy Snowflake Cortex Intelligence applications using Snowflake Notebooks, Streamlit in Snowflake, and Snowpark Python for interactive analytics and model inference
• Data Modeling: Understanding of dimensional modeling and data modeling best practices
• Domain Exposure: Experience working with structured and semi-structured datasets in the Pharma or Healthcare domain

Join Us

Join PharmSight and contribute to building modern commercial data platforms that power advanced analytics and AI-driven decision-making for global pharma organizations. If you are a hands-on engineer passionate about scalable data solutions and real-world impact, we’d love to hear from you. Interested?

Apply now and our team will get back to you soon!