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Chief Research Data Architect
2 months ago
We are seeking a visionary Chief Research Data Architect to join our team at InsideHigherEd. As a key member of our organization, you will play a critical role in shaping the research technology and data landscape for our institution.
Key Responsibilities- Collaborate with researchers across various disciplines to understand and gather requirements for data-driven research and scholarship.
- Develop and implement data architectures to support the scalability, flexibility, and performance of data pipelines, ETL processes, and real-time and batch processing requirements for HPC, ML, and AI applications.
- Work closely with internal peers and campus partners to understand local research and data support needs and develop supportive data services.
- Continually assess and evolve the UCLA research technology landscape and collaborate with key stakeholders to develop supporting programs and processes.
- Develop and publish white paper strategies to facilitate campus planning and collaboration.
- 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 various 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.
- Demonstrated experience assessing and engaging third-party vendors and products.
- 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.
- 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.
- PhD in Computer Science, Engineering, Data Science, or related field.
- 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.
We offer a competitive salary and benefits package, as well as opportunities for professional growth and development.
