About Us:
UCLA’s Office of Advanced Research Computing (OARC), a dynamic department within the Office of the Vice Chancellor for Research and Creative Activities (ORCA), is seeking a visionary Chief Research Data Architect (CRDA). This is a unique opportunity to join a leading R1 university and play a pivotal role in advancing data-driven research and scholarship. If you have a passion for data science, AI, HPC, and cloud computing, and excel in building strong relationships across diverse campus communities, we want to hear from you!
Position Overview:
As the Chief Research Data Architect, you will leverage your extensive data engineering background and collaborative experience with researchers to help build UCLA’s next-generation research data and computing environment. Your role will be crucial in creating supportive data services that enable cutting-edge academic research. You will work closely with UCLA researchers, faculty-led research committees, and various campus partners to understand and address university research and data support needs.
Why Join Us:
- Impactful Work: Play a key role in shaping the research technology and data landscape at a leading R1 university.
- Collaborative Environment: Work with a diverse group of researchers, faculty, and campus partners.
- Professional Growth: Opportunities for continuous learning and professional development in a cutting-edge research environment.
- Great benefits: Employee Value Proposition of benefits and perks for becoming a UCLA Bruin.
If you are a visionary leader with a passion for enabling data-driven research and scholarship, we encourage you to apply. Join us in shaping the future of research at UCLA!
Required:
- 10 Years Relevant work experience in data engineering, data infrastructure implementation, and data architecture development in complex data environments in a research or academic setting.
- 7 Years Experience designing architectures to support a variety of data types and structures, including structured and unstructured data, and sensitive data.
- 7 Years Experience with big data platforms like Hadoop and Spark and understanding of SQL and NoSQL databases.
- 7 Years Experience with cloud-based data platforms and services, such as AWS (Amazon Redshift, S3, EMR), Azure (Azure Data Lake, Databricks), or Google Cloud Platform (BigQuery, Dataflow).
- Advanced communication and collaboration skills, with the ability to engage and influence stakeholders at all levels, including the highest levels of leadership.
- Proven leadership and management skills, with a track record of successfully organizing and leading cross-functional teams.
- Expertise in architecting and maintaining robust and repeatable data models, data infrastructure and platforms that support the scalability, flexibility, and performance to support data pipelines, ETL processes, and real-time and batch processing requirements for HPC, ML, and AI applications.
- Demonstrated experience assessing and engaging third-party vendors and products, including selection of solutions partners on medium to large-scale technical projects through an RFP process.
- Expertise with endpoint, edge and cloud architectures and the application of data communication, flow, storge standards.
- Expertise optimizing data pipelines and workflows for efficiency and cost-effectiveness, leveraging cloud-based technologies such as AWS, Azure, or Google Cloud Platform, and orchestration tools such as Apache Airflow.
- Expertise in traditional and leading-edge high-performance computing, data governance, compliance, accessibility, and security for research data.
- Familiarity with machine learning frameworks, such as TensorFlow and PyTorch.
- Proficiency in data processing frameworks like Apache Spark and Databricks, and workflow management tools like Apache Airflow.
- Excellent problem-solving, analytical skills, communication skills, verbal and written.
- Knowledge of programming languages such as Python and SQL.
Preferred:
- Contributions to open-source projects or community involvement. Experience in architecting solutions for generative and traditional AI models. Direct data science and AI project experience and/or contributions.