Job Information
BeiGene Director, Data Engineering in Emeryville, California
The Director, Data Engineering, will lead a team of data engineers responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support data products, advanced analytics, machine learning models, and business intelligence initiatives. This role requires strong leadership skills, a deep understanding of data architecture, and the ability to drive strategic projects that maximize the value of the organization’s data assets.
Lead and manage a team of data engineers, with the scope and size of the team varying based on the level of the role.
Oversee the design and development of data pipelines and data infrastructure to support data-driven initiatives.
Collaborate with data scientists, software engineers, and business stakeholders to define and deliver robust data solutions.
Drive architectural decisions for data systems, ensuring scalability, performance, and data governance compliance. The degree of strategic oversight will scale according to the position.
Provide mentorship to team members and promote best practices in data engineering, with a stronger emphasis on organizational impact at the Director level.
Implement and advocate for data quality, data governance, and security best practices across the data platform.
Evaluate emerging data technologies and provide recommendations to enhance the data infrastructure, with greater influence and responsibility expected for the Director position.
Foster a culture of innovation, continuous improvement, and collaboration.
Ensure adherence to DevOps and MLOps practices, including CI/CD for data pipelines, containerization, and cloud deployments.
Engage in project planning, resource allocation, and risk management, with the complexity of oversight scaling with the level of the role.
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
10+ years of experience in data engineering or software engineering, with 5-8 years in a leadership role managing complex projects and larger teams.
Strong proficiency in data engineering tools and technologies, such as Apache Spark, Hadoop, Kafka, and cloud-based platforms (AWS, Azure, or GCP).
Hands-on experience with data modeling, ETL processes, and distributed data processing frameworks.
Proficiency in programming languages like R, Python, Java, and expertise in SQL.
Solid understanding of data architecture principles, microservices, and data governance frameworks.
Excellent problem-solving skills and ability to drive solutions in a fast-paced environment.
Strong communication and collaboration skills, with a proven ability to work with both technical and non-technical stakeholders.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.