Biotech Data Engineer (1120271)

The Judge Group is seeking an experienced Biotech Data Engineer to design, build, and maintain scalable data platforms that support analytics, AI/ML, and reporting across commercial functions. This role will focus heavily on Azure Databricks–based architectures and will play a key role in advancing the company’s data and AI strategy.

Responsibilities:

• Design, build, and maintain scalable, reliable, and cost‑efficient data pipelines using Azure Databricks to support analytics, machine learning, data science, and operational use cases
• Lead data engineering initiatives that enable AI/ML models, LLM integrations, and AI‑driven applications, ensuring alignment with enterprise and business priorities
• Architect and implement data integration frameworks across AdTech and MarTech ecosystems, including Google Analytics, media campaign platforms, Salesforce, and third‑party marketing APIs
• Manage and optimize data ingestion, transformation, and storage using Python, PySpark, and SQL
• Integrate structured and unstructured data sources from internal and external systems
• Design and maintain API integrations, including Python‑ and PySpark‑based services and AI/LLM‑powered APIs for advanced analytics and automation
• Administer and maintain Azure data platforms (Databricks, Azure Data Factory, Azure DevOps) to ensure reliability, security, and operational excellence
• Ensure data quality, integrity, and consistency through validation, monitoring, and alerting
• Implement and enforce data governance, security, and compliance standards in partnership with IT, InfoSec, and data governance teams
• Partner with analytics, marketing, commercial operations, and core technology teams to deliver fit‑for‑purpose commercial data products
• Translate data and AI strategy into technical architecture, design documentation, and implementation roadmaps
• Participate in architecture discussions, design reviews, CI/CD workflows, and Agile ceremonies
• Monitor and optimize performance, scalability, and cost across Azure cloud environments
• Develop and maintain architecture diagrams, pipeline specifications, and technical documentation
• Evaluate and recommend new Azure services, frameworks, and AI integration tools
• Drive automation, observability, and standardization across data workflows

Requirements:

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
• 5+ years of experience in data engineering, data architecture, or cloud platforms
• Prior pharma or biotech industry experience, preferably within commercial data (sales, marketing, market access, payer data)
• Strong hands‑on experience with Azure Cloud, including Databricks, Azure Data Factory, and Azure DevOps
• Advanced skills in Python, PySpark, and SQL
• Experience building and consuming API‑based integrations in ETL pipelines
• Experience integrating AI models and APIs (e.g., OpenAI API, Databricks AI models)
• Ability to independently design end‑to‑end data pipelines while following architectural best practices
• Strong collaboration skills with the ability to translate business needs into technical solutions
• Experience with Databricks Unity Catalog or Databricks One
• Familiarity with MarTech and AdTech platforms and data ecosystems
• Knowledge of consumer, patient, or HCP data
• Experience with identity resolution platforms (e.g., LiveRamp, Acxiom, Experian)
• Experience with Customer Data Platforms (CDPs)
• Exposure to marketing automation tools