Data Engineer

Certain terms and conditions of employment for this position, including the rate of pay, benefits, etc., are currently subject to negotiation with the appropriate union.

Applies skills as a seasoned, experienced data/information management professional with full understanding of industry practices and campus / medical center / OP and department methodologies, policies and procedures to resolve complex and wide-ranging issues where analyses of situations or data require a review of a variety of factors. Demonstrates competency in selecting methods and techniques to obtain solutions.

Specifically, the Data Analyst will work with EIA (Enterprise Information Analytics), data governance staff, business analysts, end users, data owners, and technical teams to:

• Collaborate with business and technical stakeholders to understand data, reporting, and analytics needs.
• Design, develop, and deliver efficient, standards-based analytics solutions that support operational and strategic decision-making.
• Translate data into actionable insights and recommendations to support business operations, performance improvement, and organizational objectives.
• Develop and maintain dashboards, reports, and visualizations that monitor key business metrics and provide meaningful information to leadership and operational teams.
• Participate in the design and implementation of analytic solutions, including data acquisition processes, business rules processing, data aggregation, and reporting methodologies.
• Support the development and maintenance of data pipelines, ETL workflows, and data integration processes using tools such as SQL, SSIS, DataStage, Github, Databricks, Azure Data Factory, or similar technologies.
• Analyze, design, develop, test, document, and support data warehouse and analytics solutions.
• Collaborate with data modelers, architects, and integration teams to support data architecture initiatives and contribute to end-to-end data and information delivery solutions.
• Utilize SQL and related technologies to extract, transform, validate, and optimize data for reporting and analytics purposes.
• Leverage Epic and other enterprise systems to extract, analyze, validate, and interpret healthcare data to support operational improvement and business objectives.
• Perform analysis of complex datasets, identify trends, develop visualizations, and communicate findings in a clear and compelling manner.
• Ensure data integrity and accuracy by identifying data anomalies, troubleshooting issues, and supporting continuous improvement of data quality processes.
• Provide technical expertise in data storage structures, data extraction, data transformation, data cleansing, and reporting methodologies.
• Support and use analytics and business intelligence technologies while assisting in the education of staff and customers regarding data, reporting, and analytics capabilities.
• Assist in troubleshooting complex technical issues and partner with senior staff to resolve escalated problems.
• Participate in data governance activities and support enterprise data standards, definitions, and stewardship practices.
• Collaborate with stakeholders to identify opportunities to improve reporting processes, data quality, reporting performance, and user adoption.
• Support the development and maintenance of metadata, business definitions, technical documentation, and data dictionaries.
• Research emerging analytics, reporting, and data management technologies and support the team in product evaluations, pilots, and proof-of-concept activities.
• Participate in dissemination of best practices, standards, and process improvements across the analytics community.

• Contribute to project planning activities including requirements gathering, effort estimation, testing, implementation, and post-production support.

The Enterprise Information and Analytics Health Operations team operates to stay abreast of current and emerging data management technologies and trends and advice on how they can be used to support business and technology objectives. The Data Engineer will analyze and create information assets that support UCSF Core Services within Health Operations while also contributing to broader Enterprise Information Analytics initiatives across Adult, Benioff Children's Hospitals, Ambulatory, and Network domains. The successful candidate will be customer-focused, possess strong analytical and communication skills, and demonstrate experience developing enterprise data and analytics solutions in a collaborative healthcare environment.

At UCSF, collaboration and innovation are at the heart of our mission — in our hospitals and clinics, classrooms, labs, and offices. To advance excellence in support of patient care, research, and education, we are strengthening our on-site presence across the university. As part of this commitment, most IT teams are expected to work in some capacity to support campus-based work. This role will be expected to work onsite on a rotational or alternative basis as determined by the hiring manager. Attendance at onsite meetings, events, and other work activities may be required as scheduled by management.

Department Overview

As a preeminent health sciences campus and health system, the University of California, San Francisco (UCSF) is at the forefront of creating new knowledge from the exploding volume of clinical, discovery, and education data that it creates and manages. UCSF believes that the ability to leverage these data assets is an important differentiator for an academic healthcare center and is critical to our drive toward Precision Medicine and the execution of key UCSF strategies for the Clinical Enterprise. These strategies include supporting better population health by improving the quality of care and population health of the University of California health system’s 14 million patients.

The Enterprise Analytics Information – Health Operations department functions as the liaison between the customer or partners in the organization and technical resources to provide optimal analytic solutions to solve problems, answer questions, deliver insights, and meet the needs of our customers. Key partners include clinical, financial, administration, and campus domains. The team is involved in strategic and operational activities to both inform and drive change in behaviors and ultimately outcomes through use of data and information. The team operates in a cross functional manner, crossing domains to implement integrated work as needed.

The University of California San Francisco (UCSF) Department of Information Technology is seeking a qualified individual to lead the design, analysis, presentation and dissemination of data, information, and knowledge critical to the performance of UCSF enterprise wide.

Enterprise Information Analytics vision is advancing UCSF’s ability to care, heal, teach, and discover by providing ubiquitous access to relevant and high-quality information and analytics. We do this by working with our clinical, research, education, and business customers to organize, integrate and govern UCSF’s information assets and then develop targeted data sets and analyses that provide important insights.

REQUIRED QUALIFICATIONS

• Bachelor's degree in related area and/or equivalent experience/training.
• 3+ years of experience designing, developing, testing, and implementing secure, scalable, and high-performance BI and analytic solutions; at least 3-5 years of experience as a Tableau / Power BI Developer or other BI tool
• 1-3 years of experience in skills associated with software specification, design, modification, implementation and deployment of medium-scale scope.
• 2 years of experience with dimensional data modeling and relational databases
• 2 years of experience in SQL
• Self-motivated, detail-oriented professional with the ability to work independently and collaboratively, manage competing priorities, and meet deadlines.
• Strong critical thinking and problem-solving skills to manage complex information, assess problems, and develop and effective solutions.
• Strong analytical and design skills, including the ability to abstract information requirements from real-world processes to understand information flows in computer systems.
• Ability to represent relevant information in abstract models. Critical thinking skills and attention to detail.
• Ability to communicate effectively, both verbally and in writing, with technical and non-technical audiences at all levels of the organization.
• Demonstrated interpersonal, collaboration, and customer service skills with the ability to work effectively with diverse team members and stakeholders.
• Strong interpersonal, collaboration, and relationship-building skills with the ability to work effectively across business and technical teams.
• Proficient in developing technical specifications, presentations, training materials, user documentation, and technical documentation.
• Demonstrated success with software development lifecycle for enterprise-wide BI projects and ability to assess and solve technical problems
• Demonstrated ability to understand domain needs and how systems can support those needs. Demonstrated ability to participate in conversion and system implementation plans.

• Detail oriented, with ability to manage time and organize competing priorities.

PREFERRED QUALIFICATIONS

• Master’s degree in related area and / or equivalent experience / training.
• Epic Clarity Certification
• Ability to produce high-quality reports and documentation.
• Experience with analytics and data processing technologies such as Python, R, Databricks, or similar tools.
• 1 year of experience in BI and analytics in healthcare
• Experience in the analysis, design, development, and implementation of ETL workflows using tools such as SQL, DataStage, Github, Databricks, SSIS, etc.
• Good project leadership and management skills.
• Experience in Agile/Scrum development methodology
• Experience creating and maintaining data visualizations standards
• Familiarity with data model patterns in one or more common business or academic domains.
• Familiarity with logical data design and data mapping or data conversion.
• Familiarity with data quality and governance issues and requirements.
• Thorough knowledge of relevant rules, regulations and industry standards and best practices