Key Responsibilities

Data Engineering & Pipeline Development

• Design, develop, and maintain scalable ETL/ELT pipelines using Python, SQL, Databricks, and PySpark.

• Build reliable data ingestion and transformation workflows across multiple enterprise data sources.

• Develop and optimize data models to support analytics, reporting, and intelligent applications.

• Ensure data quality, consistency, reliability, and performance across data platforms.

Database & API Integration

• Work with Microsoft SQL Server (MSSQL) and Azure Database for PostgreSQL.

• Develop and integrate REST APIs to connect data platforms and enterprise applications.

• Design efficient database structures, queries, and data processing workflows.

• Support secure and scalable data exchange between systems.

Cloud Data Platforms & Modern Architecture

• Work with Microsoft Azure and modern cloud-based data engineering services.

• Contribute to Microsoft Fabric implementations, including OneLake, Lakehouse, Data Factory, and Fabric Warehouse.

• Build and maintain scalable and reusable data architecture.

• Collaborate with engineering teams to improve deployment and integration workflows.

AI, Automation & Analytics

• Support AI/ML integration and intelligent data processing capabilities.

• Contribute to real-time data processing and event-driven architectures where required.

• Collaborate on analytics and visualization solutions using Power BI, Tableau, or similar tools.

• Explore opportunities to improve data workflows through automation and AI capabilities.

Required Technical Skills & Experience

• 5–10 years of experience in data engineering or related engineering roles.

• Strong programming experience in Python and SQL.

• Hands-on experience with Databricks and PySpark.

• Experience with Microsoft SQL Server (MSSQL).

• Experience with Azure Database for PostgreSQL.

• Strong understanding of ETL/ELT pipelines and data modeling.

• Experience developing and integrating REST APIs.

Preferred Skills & Experience

• Knowledge of Microsoft Fabric, including OneLake, Lakehouse, Data Factory, and Fabric Warehouse.

• Familiarity with the Microsoft Azure ecosystem.

• Experience with Azure DevOps, Git, and CI/CD pipelines.

• Exposure to Azure Data Factory, Azure Functions, and Azure cloud services.

• Basic knowledge of React, HTML, and CSS.

• Experience with Power BI, Tableau, or other data visualization tools.

• Exposure to AI/ML integration, real-time data processing, or Apache Kafka.

Domain Preference

Experience in any of the following domains will be preferred:

• Clinical Supply Chain

• Healthcare & Pharmaceutical Supply Chain

• Inventory & Warehouse Management

• Procurement, Logistics & Distribution

• Enterprise Supply Chain Platforms

The Opportunity We Offer

• Product Innovation: Build a next-generation AI-powered clinical supply chain platform.

• Modern Technology: Work with Databricks, PySpark, Microsoft Fabric, Azure, and advanced data technologies.

• Real-World Impact: Solve complex data engineering challenges across pharmaceutical and healthcare supply chains.

• AI & Automation: Contribute to intelligent automation, advanced analytics, and AI-driven capabilities.

• Growth: Collaborate with a product engineering team focused on innovation and scalable technology.

Join Boston Insights

If you're passionate about data engineering, modern data platforms, and building intelligent technology solutions, we'd love to hear from you.

Share your updated resume through our application form to explore this opportunity.

Let's build something intelligent. Let's build the future of supply chains.