Chief Research Data Architect - Indiana Biosciences Research Institute

Department Summary

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

The UCLA Office of Advanced Research Computing (OARC), a department within the Office of the Vice Chancellor for Research and Creative Activities (ORCA), is seeking a visionary Chief Research Data Architect (CRDA) with a passion for enabling data-driven research and scholarship at an R1 university with a focus on data science, AI, HPC, and cloud computing. This role requires strong relationship building and excellent communications skills across a variety of campus communities to create trust among UCLA researchers and the UCLA research data enterprise.

As a Chief Research Data Architect, the ideal candidate will leverage an extensive data engineering background and experience collaborating with data scientists to help build UCLA's next generation research data and computing environment and collaborate with stakeholders to create supportive data services to enable cutting-edge academic research. The ideal candidate will have proven skills in collaborating with the research community and key stakeholders to create supportive data services to enable cutting edge academic research. This will include continually assessing and evolving the data-driven technology landscape as academic research needs change and technology evolves. This role offers a unique opportunity to play a key role in shaping the research technology and data landscape for UCLA.

The Chief Research Data Architect will collaborate directly with UCLA researchers across a multitude of disciplines and faculty-led research committees, such as the Institute for Digital Research and Education (IDRE) and DataX, to understand and gather requirements and collaborate on ongoing strategic directions. This role will work closely with internal peers across the OARC management team, OARC research experts and computational scientists, and a variety of campus partners, including, but not limited to IT Services, the Office of the Chief Information Security Officer, the Library, Academic Organizations, Professional Schools, and department level IT to understand local research and data support needs. In partnership with collaborators, the CRDA will publish and present white paper strategies that facilitate campus planning.

Additionally, the position will continually assess and evolve the UCLA research technology landscape and collaborate with key stakeholders within and outside of OARC to develop the supporting programs and processes that help enable the strategic research outcomes as defined by UCLA.

The Chief Research Data Architect reports to the Executive Director, OARC, and is part of the OARC Management team.

Salary & Compensation

*UCLA provides a full pay range. Actual salary offers consider factors, including budget, prior experience, skills, knowledge, abilities, education, licensure and certifications, and other business considerations. Salary offers at the top of the range are not common. Visit UC Benefit package to discover benefits that start on day one, and UC Total Compensation Estimator to calculate the total compensation value with benefits.
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, storge 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. (Preferred)

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

https://universityofcalifornia.marketpayjobs.com/ShowJob.aspx?EntityID=38&jobcode=TBD_1693#J-18808-Ljbffr