Vice President, Data Engineering

About the role

Lead the development and implementation of AI-driven solutions in the pharmaceutical industry to improve patient care through personalized omnichannel communications. Drive the integration of Large Language Models (LLMs) into software development and oversee the creation of Retrieval-Augmented Generation (RAG) applications.

Collaborate closely with product, sales, and marketing teams to architect and guide engineering, API, ML, DevOps, and reporting teams in building a scalable and innovative product. Promote best practices in Agile methodologies and CI/CD processes to ensure efficient, high-quality product delivery and continuous improvement.

Oversee and optimize a complex technology stack, including Snowflake, Terraform, dbt, Docker, Azure SQL, Synapse, Azure, Python, SQL, Spark, and Azure container apps. Ensure data accuracy, scalability, and efficiency in data pipelines and AI models. Lead research and implementation of emerging AI and ML technologies to drive business innovation and competitive advantage.

Develop and maintain strategic roadmaps for AI-driven data engineering initiatives aligned with business goals. Provide technical leadership and mentorship to engineering teams, fostering innovation and collaboration. Ensure compliance with industry regulations and best practices related to data security and privacy.

Requirements

• Master's degree or foreign academic equivalent in Computer Science, Information Technology, or a related field.
• 8 years of experience in the job offered or a related occupation including Data Consultant, Data Director, or related experience.
• 6 years of experience with data engineering, ML (Machine Learning), Snowflake, Terraform, Docker, Python, SQL, and Azure.

Schedule

40 hours per week.

Work Location

Position may telecommute / work remotely from anywhere in the U.S.