Analytics Engineer

UC Santa Cruz is a public university like no other in California, combining the experience of a small, liberal arts college with the depth and rigor of a major research university. It's known as an unconventional place where innovation and experimentation is part of the campus's DNA. That playful, bold spirit still thrives today, all on a campus renowned as among the most beautiful in the world.

Department Overview

The Office of Budget Analysis and Planning’s Data Management team oversees and supports campus data warehouse services in partnership with Information Technology Services. For more than 20 years, the campus data warehouse has grown and matured in response to campus-wide reporting needs across 35+ subject areas from 50+ data sources. Reports available through the reporting tool InfoView (SAP Business Objects), both standard and ad hoc, are widely used on campus for both daily operational information and longitudinal trend analysis. The topical areas of reporting are varied and include enterprise system reporting, such as financial operations, personnel, payroll, academic information, philanthropic donations, campus facilities, etc., as well as unit-specific operations such as dining point of sale, purchasing turn-time, equipment management, etc. In 2022, the department co-sponsored and funded, the transformative initiative to modernize the data warehouse and implement a cloud-based common data platform.

Job Summary

UC Santa Cruz has launched a multi-year strategic initiative with the objectives of modernizing the existing campus data warehouse and streamlining data integration with and across campus enterprise systems. The Common Data Platform (CDP) initiative is sponsored by campus leadership to ensure the campus' data assets support the mission and vision of the University. The CDP will transform the information experience, empower business units, and provide stewardship over shared campus resources to support student and employee success. Analytics Engineers sit at the intersection of business units and data engineering and are responsible for bringing robust, efficient, and integrated data models and products to life. Analytics Engineers speak the language of business units and technical teams, translating data insights and analysis needs into models powered by the CDP. Successful Analytics Engineers can blend business process understanding with technical expertise and transition between business processes and data development. Under the supervision of the Lead Analytics Engineer, Data Management, the Analytics Engineer has responsibilities across the entire data stack. These responsibilities include building partnerships with campus constituents and subject matter experts and delivering trusted, curated, accurate data sets, semantic modeling, and data integrations to meet the information needs of the campus.

Budgeted Salary: $68,400-$124,000/annually. Salary commensurate with skills, qualifications and experience.

Job Duties

60%% - Project and Service Management. Participates in small to medium-sized complex projects and teams, including:

Collaborating with team members and business partners to collect business requirements, define successful analytics and information outcomes, and design supporting data models.
Transforming raw data into well-designed, documented, tested data models and maintaining these models over time, keeping pace with the organization's dynamic needs
Adopt software engineering best practices like version control, unit tests, and in-line documentation to develop robust data models and data marts in collaboration with business partners and stakeholders. Maintain models in the event of unforeseen disruptions in data pipelines.
Work with various Business Information (BI) tools to assist in information delivery through dashboards, reporting, and data sharing.
Monitoring and communicating project status to the appropriate individuals.
Assists with the adoption of naming conventions and coding standards.
Participates in code reviews and pull request sessions with stakeholders, partners, and other interested parties.
Support production operations for CDP.

20%% - Universe Development/Maintenance. Maintain existing SAP Business Objects universes to support reporting/information business needs. Responsibilities may include:

Recommend appropriate actions based on data integrity reviews
Define new objects, update data definitions, testing, and validation of universe layer
Bring in new data elements, ensure accurate joins, conduct validation, and usability testing and analysis

20%% - Client engagement/support

Providing outreach and support across all services and products
Participates in Open Labs and or Office Hours to engage and support clients
Collaboratively builds knowledge regarding subject matter
Assists with building reports, dashboards, integrations and other data products

Required Qualifications

Bachelor's degree in related area and/or equivalent experience/training
Demonstrated hands-on engagement, such as performing analysis or writing complex queries and models.
Ability to develop and leverage subject matter expertise, knowledge of underlying data structures and SQL skills to produce modular, modeled, trusted, documented, reusable data sets.
Understanding and skill in complex process and systems requirement documentation standards, such as Use Case modeling, User Story creations, and narrative description.
Knowledge and ability to participate and support the adoption of agile development methodology.
Skillful and creative in troubleshooting information processes, data analysis, data lineage, and identification of data quality issues in relation to assigned responsibilities.
Ability to evaluate data and analytically based problems to determine the best solutions for clients and stakeholders.
Thorough knowledge with business analysis techniques and compliance with applicable policy and regulation, such as data security best practices and appropriate use of information, including the handling of confidential and restricted data (“FERPA”,”PII”, etc.) as well as information security practices.
Knowledge of information architecture, including common data structures, models, design, and processing methodologies.
Experience with version control platforms such as Gitlab or GitHub
Demonstrated effective oral communication skills with the demonstrated ability to communicate technical information to technical and non-technical personnel at various organizational levels.
Demonstrated interpersonal skills.
Self-motivated with the ability to work independently.
Ability to work as a member of a team.

Preferred Qualifications

Experience with dimensional modeling concepts or similar approaches in producing useful information for analysis and reporting.
Experience with cloud data warehousing technologies associated with the modern data stack.
Two or more years using dbt to deliver and maintain clean, transformed data models ready for analytics.

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