Biotech Data Engineer

Arcutis Biotherapeutics, Inc. is a pioneering medical dermatology company focused on revolutionizing the treatment of serious skin diseases. They are seeking a Biotech Data Engineer to design, build, and maintain scalable data pipelines and architectures, enabling analytics and AI/ML reporting across commercial functions.

Responsibilities:

• Design, build, and maintain scalable, reliable, and cost-efficient data pipelines using Azure Databricks in support of analytics, machine learning, data science, and operational use cases
• Lead data engineering initiatives that enable AI/ML model development, LLM integrations, and AI-driven applications while ensuring scalability and alignment with enterprise and business priorities
• Architect and implement data integration frameworks across diverse Adtech and Martech ecosystems, incorporating Google Analytics, media campaign data, and third-party marketing APIs like Salesforce
• Manage and optimize data ingestion, transformation, and storage processes using SQL, Python, and PySpark to integrate structured and unstructured data sources
• Design and maintain API integrations with internal and external systems, including Python- and PySpark-based services and AI/LLM-powered APIs for advanced analytics and automation
• Administer and maintain Azure-based data tools and platforms (e.g., Databricks, ADF) to ensure operational excellence, reliability, and security
• Collaborate with internal stakeholders and external partners to evolve data platform design and architecture that supports advanced analytics, personalization, marketing intelligence, and marketing automation
• Execute against the company’s data and AI strategy by translating strategic goals into technical architecture, design and requirement documents, and implementation roadmaps
• Ensure data quality, integrity, and consistency through robust validation, monitoring, and alerting mechanisms within Azure Databricks
• Implement and enforce data governance, security, and compliance standards in collaboration with IT, InfoSec, and data governance teams
• Partner with analytics, marketing, commercial operations, and core technology/cybersecurity teams to deliver fit-for-purpose commercial data products
• Monitor and optimize data infrastructure costs, performance, and scalability across Azure cloud environments
• Develop and maintain architecture documentation, pipeline specifications, and design diagrams for transparency and knowledge sharing with technical and business stakeholders
• Participate in architecture discussions, design reviews, and CI/CD workflows to ensure high-quality engineering and deployment practices as part of an Agile engineering team
• Continuously evaluate and recommend new Azure services, designs, improvements, frameworks, and AI integration tools to enhance our data platform
• Drive automation, observability, and standardization across data workflows to improve efficiency and reduce manual intervention
• Complete all job duties in compliance with company policy, SOPs, safety rules, and applicable federal, state, and local regulations

Requirements:

• Bachelor of science degree required
• A minimum of 5 years transferable working experience in the area of operational support of a Data Engineering, Data Architecture, or Cloud Platforms function preferred
• Experience with Azure Cloud (Databricks, DevOps, DataFactory)
• Pharma / biotech domain experience, specifically within the commercial data space (sales, market access / payer, marketing)
• Strong hands-on python, pyspark, and SQL skills
• Direct experience with building and leveraging API integrations in ETL pipeline development
• Experience integrating with current best-in-class AI models and APIs like OpenAI API, Databricks AI models, etc
• Self-driven with ability to independently design end-to-end data pipelines while ensuring architectural best practices
• Ability to collaborate with a broad set of stakeholders to evaluate the business need and construct a technical design that can enable stakeholder priorities
• Travel up to 20%
• Strong knowledge of and experience with maximizing business value using Databricks Unity Catalog or Databricks One capabilities
• Familiarity with tools and practices in the Martech and Adtech landscape
• Knowledge of Consumer, Patient, or HCP data ecosystems
• Experience with identity providers like LiveRamp, Acxiom, Experian, etc
• Experience with custom-built or third-party Customer Data Platforms (CDP)
• Experience with marketing automation tools