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