Chief Research Data Architect

$124,600 - $212,000/Yr

Unclassified - Los Angeles, CA

Part-time - Senior

Los Angeles, CA

About the position

The UCLA Office of Advanced Research Computing (OARC) is seeking a visionary Chief Research Data Architect (CRDA) to lead the development of data-driven research and scholarship initiatives at UCLA. This role is pivotal in shaping the research technology and data landscape for the university, particularly in the realms of data science, artificial intelligence (AI), high-performance computing (HPC), and cloud computing. The CRDA will be responsible for building and enhancing UCLA's research data and computing environment, ensuring that it meets the evolving needs of the academic community. This position requires a strong emphasis on relationship building and communication skills to foster trust among researchers and stakeholders across various campus communities. The Chief Research Data Architect will leverage an extensive background in data engineering and collaborate closely with data scientists to create supportive data services that facilitate cutting-edge academic research. This includes continually assessing and evolving the data-driven technology landscape as academic research needs change and technology advances. The CRDA will work directly with researchers from diverse disciplines and faculty-led research committees, such as the Institute for Digital Research and Education (IDRE) and DataX, to gather requirements and collaborate on strategic directions. The role also involves publishing and presenting white paper strategies that aid in campus planning and developing programs and processes that support strategic research outcomes as defined by UCLA. As part of the OARC management team, the Chief Research Data Architect will report to the Executive Director of OARC and will be instrumental in shaping the future of research technology at UCLA. This position offers a unique opportunity to influence the research data enterprise and contribute to the university's mission of education, research, and service through innovative and sustainable technology practices.

Responsibilities

• Lead the development of UCLA's research data and computing environment.
• Collaborate with data scientists to create supportive data services for academic research.
• Assess and evolve the data-driven technology landscape in response to changing academic needs.
• Engage with UCLA researchers and faculty-led committees to gather requirements and strategic directions.
• Publish and present white paper strategies for campus planning.
• Work closely with internal peers and campus partners to understand local research and data support needs.
• Develop supporting programs and processes to enable strategic research outcomes.

Requirements

• 10 years of 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 of experience designing architectures to support a variety of data types and structures, including structured and unstructured data, and sensitive data.
• 7 years of experience with big data platforms like Hadoop and Spark and understanding of SQL and NoSQL databases.
• 7 years of experience with cloud-based data platforms and services, such as AWS, Azure, or Google Cloud Platform.
• Advanced communication and collaboration skills, with the ability to engage and influence stakeholders at all levels.
• 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 scalability, flexibility, and performance for data pipelines, ETL processes, and real-time and batch processing requirements.
• 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, and storage standards.
• Expertise optimizing data pipelines and workflows for efficiency and cost-effectiveness, leveraging cloud-based technologies and orchestration tools.
• Expertise in 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 and analytical skills, with strong verbal and written communication skills.
• Knowledge of programming languages such as Python and SQL.

Nice-to-haves

• 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.

Benefits

• Comprehensive health insurance coverage starting on day one.
• Retirement savings plan with 401k options.
• Tuition reimbursement for further education.
• Flexible scheduling options including hybrid work arrangements.
• Professional development opportunities and resources.