Data Engineer (Flex Hybrid).

$95,900 - $222,100/Yr

University of California - Los Angeles, CA

Full-time

Los Angeles, CA

Educational Services

About the position

As a Data Engineer on the Data Architecture team at UCLA Health, you will play a pivotal role in driving technology initiatives aimed at enhancing health informatics and analytics within the health sciences sector. Your primary focus will be on improving the usability, performance, and overall architecture of the Data Infrastructure. This includes the development of reliable, large-scale data processing pipelines, foundational architectural components, reusable frameworks, and data models that support the Enterprise Data Warehouse, Data Lakes, Feature Stores, and Machine Learning Platform. Your responsibilities will involve a high level of technical acumen in planning, designing, developing, implementing, and administering data-based systems that acquire, prepare, store, and provide access to data and metadata. You will be tasked with maintaining and optimizing these systems, as well as migrating data and systems as necessary. Ensuring the integrity and completeness of data and workflows will be crucial, as will managing and developing data practices, databases, and information systems, along with guidelines, dictionaries, registries, and services. Your role may also include interpreting scientific research data artifacts and mediating across science and technology domains, ensuring long-term data care. As an information architect and data steward, you will design systems, data products, and data production processes with a strong emphasis on data curation, data exchange, data security, data integrity, and the overall information environment. You will be responsible for (re)evaluating frameworks, strategies, standards, and standards-making activities. Your work may involve collaboration with a project-level data repository, a center, or an archive. This position offers a unique opportunity to contribute to the development of UCLA Health's Data Platform and products, advancing analytics for one of the nation's leading healthcare organizations. The role is flex-hybrid, requiring you to be onsite at least once a month, with the understanding that there are no reimbursements for travel to the home office location. Each employee must complete a FlexWork Agreement with their manager to outline arrangement parameters, which will be regularly evaluated and are subject to termination.

Responsibilities

• Develop reliable, large-scale data processing pipelines.
• Create foundational architectural components and reusable frameworks.
• Design data models to support Enterprise Data Warehouse, Data Lakes, Feature Stores, and Machine Learning Platform.
• Plan, design, develop, implement, and administer data-based systems.
• Maintain and optimize data systems and migrate data as needed.
• Ensure integrity and completeness of data and workflows.
• Manage and develop data practices, databases, and information systems.
• Interpret scientific research data artifacts and mediate across science and technology domains.
• Design systems, data products, and data production processes focusing on data curation, exchange, security, and integrity.
• Reevaluate frameworks, strategies, and standards.

Requirements

• Minimum five years of software development experience.
• 2+ years experience on the data or backend systems side of software development.
• Strong industry experience in programming languages such as Python.
• Experience with orchestration tools like Airflow is required.
• Strong experience with relational databases like SQL Server or Oracle is required.
• Strong background in data warehousing and ETL principles, architecture, and implementation in large environments.
• Experience working with machine learning systems like Databricks, Feature Stores, MLOps is preferred.
• Working knowledge of leading cloud platforms like Azure, AWS, GCP; Microsoft Azure experience is preferred.
• Bachelor's degree in computer science, computer engineering, or related field from an accredited college or university.
• Master's degree preferred.

Nice-to-haves

• Experience working with Machine Learning Systems like Databricks, Feature Stores, MLOps is preferred.
• Working knowledge of leading cloud platforms like Azure, AWS, GCP; Microsoft Azure experience is preferred.