Lensa is a career site that helps job seekers find great jobs in the US. We are not a staffing firm or agency. Lensa does not hire directly for these jobs, but promotes jobs on LinkedIn on behalf of its direct clients, recruitment ad agencies, and marketing partners. Lensa partners with DirectEmployers to promote this job for UCLA Health. Description As a Data Engineer on the Data Architecture team, you will play a pivotal role in advancing health informatics and analytics in the health sciences. Your efforts will focus on enhancing the usability, performance, and architecture of the Data Infrastructure. You will design and develop reliable, large-scale data processing pipelines, foundational architectural components, reusable frameworks, and data models to support enterprise-level data ecosystems such as Data Warehouses, Data Lakes, Feature Stores, and Machine Learning Platforms. This role demands strong technical expertise in planning, designing, developing, implementing, and managing data-based systems to acquire, prepare, store, and make data and metadata accessible. You will optimize and maintain these systems, migrate data as needed, and ensure the integrity and completeness of both data and workflows. As an information architect and data steward, you will design systems, data products, and data production processes, with a strong emphasis on data curation, exchange, security, and integrity. You will also evaluate and refine frameworks, strategies, and standards. This work may include contributions to project-level repositories, centers, or archives. Key Responsibilities • Design and implement foundational data infrastructure to support the reporting, analytics, and data science needs of UCLA Health. • Build data pipelines, training datasets, and inference datasets to enable AI, Machine Learning (ML), and Generative AI use cases. • Develop efficient, scalable, and resilient pipelines to ingest data from multiple external sources. • Create Data Architecture artifacts, including documentation, data quality metrics, logs, and observability tools for pipelines. • Collaborate with cross-functional teams, including product management, analysts, and business stakeholders, to deliver scalable and usable datasets. • Lead high-priority projects by formulating strategies and overseeing policies, processes, and resources. • Elevate the technical expertise of the team through training, workshops, and presentations, fostering a culture of continuous improvement. • Represent the Data Architecture team in cross-functional meetings to assess data needs and propose innovative design solutions. • Work closely with the Manager of Data Architecture to develop and execute the technical and growth roadmap for the team. • Establish and maintain information documentation standards, such as data naming conventions and value domain descriptions. This flexible hybrid role allows for a blend of remote and on-site work, requiring presence on-site at least once a month or as needed based on operational requirements. Please note, travel to the 'home office' location is not reimbursed. Each employee will complete a FlexWork Agreement with their manager to outline expectations and ensure mutual understanding. These arrangements are periodically reviewed and may be adjusted or terminated as necessary. Salary offers are based on a variety of factors including qualifications, experience, and internal equity. The full salary range for this position is $102,500 - 227,700 annually. The University anticipates offering a salary between the minimum and midpoint of this range. This is a three year contract. Contract appointments may convert to Career appointments. Qualifications • Minimum three years of software development experience. • 5+ years' experience on the data or backend systems side of the software development. • Strong industry experience in programming languages such as Python with the ability to pick up new languages and technologies quickly. • Experience with any code-based Orchestration tools like Airflow or Luigi is required. • Strong experience with Relational databases like SQL Server or Oracle is required. • Strong background in Data warehousing and ETL principles, architecture, and its implementation in large environments. • Experience working with Machine Learning Systems like Databricks, Feature Stores, MLOps is strongly preferred. • Working knowledge on 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. UCLA Health welcomes all individuals, without regard to race, sex, sexual orientation, gender identity, religion, national origin or disabilities, and we proudly look to each person’s unique achievements and experiences to further set us apart. If you have questions about this posting, please contact support@lensa.com