Lead Data Engineer

Legend Biotech is a global biotechnology company dedicated to treating, and one day curing, life‑threatening diseases. Headquartered in Somerset, New Jersey, we are developing advanced cell therapies across a diverse array of technology platforms, including autologous and allogenic chimeric antigen receptor T‑cell, T‑cell receptor (TCR‑T), and natural killer (NK) cell‑based immunotherapy. From our three R&D sites around the world, we apply these innovative technologies to pursue the discovery of safe, efficacious and cutting‑edge therapeutics for patients worldwide.

We are seeking a Lead Data Engineer to build and operate enterprise‑grade data pipelines using Microsoft Azure as the orchestration layer and Snowflake as the enterprise data lake/warehouse. This role focuses on reliable ETL/ELT, push/pull data integration patterns, and scalable platform engineering in a GxP / validated environment.

• The Lead Data Engineer will be responsible for developing and maintaining ETL/ELT pipelines for ingesting data from various sources into our data warehouse.
• Design and build batch and incremental data pipelines using Azure‑native orchestration services to move data into and out of Snowflake.
• Support push and pull architectures across files, APIs, enterprise applications, and external partners.
• Develop curated, consumption‑ready datasets in Snowflake using standardized, reusable patterns.
• Implement data quality, and reconciliation controls within pipelines.
• Follow CI/CD and controlled deployment practices across Dev / QA / Prod environments.
• Ensure solutions meet GxP expectations for data integrity, traceability, auditability, and change control.
• Partner with Quality, Validation, and platform teams to support compliance and audit readiness.
• Data Catalog, Metadata & Governance Enablement:
• Publish and maintain data assets, schemas, and lineage in the enterprise data catalog.
• Partner with Data Governance and Business teams to support certified datasets, ownership, and usage transparency.
• Work with an end‑to‑end ownership mindset, innovate and drive initiatives through completion.
• Optimize data storage and retrieval to ensure efficient performance and scalability.
• Collaborate with data architects, data analysts and data scientists to understand their data needs and ensure that the data infrastructure supports their requirements.
• Ensure data quality and integrity through data validation and testing.
• Implement and maintain security protocols to protect sensitive data.
• Stay up‑to‑date with emerging trends and technologies in data engineering and analytic.
• Community lead to enable adoption of data and technology strategy.
• Knowledgeable in evolving trends in Data platforms and Product based implementation.
• Comfortable working in a fast‑paced environment with minimal oversight.
• Prior experience working in an Agile/Product based environment.
• Data engineering, pipelines, AI/ML development, requirements gathering with Business Partners.
• Technical delivery execution (build, test, deploy).
• Technical estimates and feasibility.
• Resource planning within Data & AI team.
• Qualify/Validate system and pipelines.
• FUT/SIT completion.
• Technical Project Management.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field (Master’s preferred).
• 7-10 years of hands‑on data engineering experience.
• Total 15+ years of IT experience.
• Strong experience with Microsoft Azure orchestration/integration services.
• Strong experience working with Snowflake as a data lake/warehouse.
• Proven experience with ETL/ELT and push/pull integration patterns.
• Experience operating in regulated or validated (GxP) environments.
• Strong SQL and data engineering fundamentals.
• Experience with enterprise data platforms and multi‑domain data architectures.
• Familiarity with CI/CD, role‑based access control, and secure data sharing.
• Experience in Data Catalog tools and implementation.
• Experience integrating ERP, manufacturing, or regulated systems.
• Strong programming skills (Python, SQL; Java/Scala a plus).
• Experience with data warehousing and lakehouse architectures.
• Hands‑on experience with ETL/ELT tools and orchestration…