Chief Research Data Architect

Department Summary

Learn more about the general tasks related to this opportunity below, as well as required skills.

Advanced Research Computing melds expert staff and technical infrastructure to amplify and accelerate the impact of UCLA research in the age of networked data and computation.

OARC expertise and resources are available to all UCLA researchers who are engaged in digital research and scholarship. We work with faculty, student, and postdoctoral researchers;

instructors; and staff and administrators.

OARC is a relationship-building organization. We enable digital scholarship through collaborations, partnerships, and networked communities to advance cutting-edge research capabilities at UCLA and beyond.

OARC supports and enhances the university mission of education, research, and service through the development and execution of innovative and sustainable technology practices, programs, services, infrastructure, policies, and partnerships.

Position Summary

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.

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!

Qualifications

• 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. (Required)
• 7 Years Experience designing architectures to support a variety of data types and structures, including structured and unstructured data, and sensitive data. (Required)
• 7 Years Experience with big data platforms like Hadoop and Spark and understanding of SQL and NoSQL databases. (Required)
• 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). (Required)
• Advanced communication and collaboration skills, with the ability to engage and influence stakeholders at all levels, including the highest levels of leadership. (Required)
• Proven leadership and management skills, with a track record of successfully organizing and leading cross-functional teams. (Required)
• 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. (Required)
• 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. (Required)
• Expertise with endpoint, edge and cloud architectures and the application of data communication, flow, storage standards. (Required)
• 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. (Required)
• Expertise in traditional and leading-edge high-performance computing, data governance, compliance, accessibility, and security for research data. (Required)
• Familiarity with machine learning frameworks, such as TensorFlow and PyTorch. (Required)
• Proficiency in data processing frameworks like Apache Spark and Databricks, and workflow management tools like Apache Airflow. (Required)
• Excellent problem-solving, analytical skills, communication skills, verbal and written. (Required)
• Knowledge of programming languages such as Python and SQL. (Required)
• 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. (Preferred)

Education, Licenses, Certifications & Personal Affiliations

• Master's Degree Computer Science, Engineering, Data Science or related field. (Required)
• PhD Computer Science, Engineering, Data Science or related field. (Required)

Special Conditions for Employment

• Background Check : Continued employment is contingent upon the completion of a satisfactory background investigation.
• Live Scan Background Check : A Live Scan background check must be completed prior to the start of employment.

Schedule

8 : 00 AM to 5 : 00 PM

Union / Policy Covered

99-Policy Covered

Complete Position Description

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