Sr. Data Solutions Analyst

University of Miami•Coral Gables, FL

About The Position

The University of Miami UMIT Department has an exciting opportunity for a Full-Time Sr. Data Solutions Analyst. The Sr. Data Solutions Analyst provides an intermediate level of designing and building relational databases for data storage or processing. Develops strategies for warehouse implementation, data acquisition and access, and data archiving and recovery. Builds data models and defines the structure, attributes, and nomenclature of data elements. May evaluate new data sources for adherence to the organization's quality standards and ease of integration. Core Responsibilities: Defines and documents the technical architecture of Power BI semantic models and objects created in collaboration with the data warehouse. Provides guidance and integration for BI products and services. Participates in the delivery of numerous key business objectives, including ease of information access, and regulatory and enterprise reporting. Works with business and system analysts, business and technical data users, data warehouse and system design developers, ETL developers, and other stakeholders to execute project tasks. Design scalable ELT processes and semantic models using SQL (views, stored procedures, window functions) and best-practice star/snowflake schemas. Translates business requirements into technical designs to meet business criteria for successful BI implementations. Facilitate discovery sessions with academic leaders to clarify requirements, define metrics, and align visualizations to strategic decisions. Deliver clear, audience-appropriate briefings, data stories, and decision memos; create training assets (how-to guides, SOPs, data dictionaries) for self-service adoption. Evaluates new data sources for adherence to the organization's quality standards and ease of integration. Translate complex statistical/machine learning results into plain language, with transparent limitations and confidence intervals. Reviews and suggests improvement to the data architecture processes, policies, and vision. Pilot and evaluate new features (e.g., Power BI Copilot, Fabric experiences, parameterized notebooks) to enhance productivity and insight quality. Explores new and emerging technologies and stays current on the capabilities of vendor products. Adheres to University and unit-level policies and procedures and safeguards University assets. Department Specific Functions: Lead end-to-end analytics initiatives for Provost priorities (e.g., student persistence/retention, time-to-degree, course demand forecasting, classroom utilization, etc.). Build predictive and prescriptive models (e.g., risk scoring, enrollment forecasting, course section optimization) using R/Python; translate outputs into decision-ready visuals in Power BI. Develop advanced semantic models to support executive dashboards and KPI scorecards with robust DAX measures. Developing data products to support enterprise KPI tracking for strategic projects. Lead initiatives to support self service analytics within the office of the provost to enhance operational efficiency. Support IRSA’s goals of sourcing all key data from the data warehouse. This list of duties and responsibilities is not intended to be all-inclusive and may be expanded to include other duties or responsibilities as necessary.

Requirements

Bachelor’s degree in relevant field required
Minimum 6 years of relevant experience required
Skill in completing assignments accurately and with attention to detail.
Ability to analyze, organize and prioritize work under pressure while meeting deadlines.
Ability to process and handle confidential information with discretion.
Ability to work evenings, nights, and weekends as necessary.
Commitment to the University’s core values.
Ability to work independently and/or in a collaborative environment.
Learning Agility: Ability to learn new procedures, technologies, and protocols, and adapt to changing priorities and work demands.
Teamwork: Ability to work collaboratively with others and contribute to a team environment.
Technical Proficiency: Skilled in using office software, technology, and relevant computer applications.
Advanced proficiency in: SQL (CTEs, window functions, dynamic SQL, performance optimization).
Power BI (data modeling, DAX, RLS, incremental refresh, bookmarks, deployment pipelines).
R/Python (tidyverse/scikit-learn, feature engineering, model evaluation, reproducible workflows)
Communication: Strong and clear written and verbal communication skills for interacting with colleagues and stakeholders.
Strong communication and data storytelling skills; proven ability to interact with senior academic leadership.
Experience translating policy and academic priorities into metrics, dashboards, and operational processes.
Any appropriate combination of relevant education, experience and/or certifications may be considered.

Nice To Haves

Higher Education experience preferred
PL-300 – Power BI Data Analyst, Microsoft Fabric certifications, etc.

Responsibilities

Defines and documents the technical architecture of Power BI semantic models and objects created in collaboration with the data warehouse.
Provides guidance and integration for BI products and services.
Participates in the delivery of numerous key business objectives, including ease of information access, and regulatory and enterprise reporting.
Works with business and system analysts, business and technical data users, data warehouse and system design developers, ETL developers, and other stakeholders to execute project tasks.
Design scalable ELT processes and semantic models using SQL (views, stored procedures, window functions) and best-practice star/snowflake schemas.
Translates business requirements into technical designs to meet business criteria for successful BI implementations.
Facilitate discovery sessions with academic leaders to clarify requirements, define metrics, and align visualizations to strategic decisions.
Deliver clear, audience-appropriate briefings, data stories, and decision memos; create training assets (how-to guides, SOPs, data dictionaries) for self-service adoption.
Evaluates new data sources for adherence to the organization's quality standards and ease of integration.
Translate complex statistical/machine learning results into plain language, with transparent limitations and confidence intervals.
Reviews and suggests improvement to the data architecture processes, policies, and vision.
Pilot and evaluate new features (e.g., Power BI Copilot, Fabric experiences, parameterized notebooks) to enhance productivity and insight quality.
Explores new and emerging technologies and stays current on the capabilities of vendor products.
Adheres to University and unit-level policies and procedures and safeguards University assets.
Lead end-to-end analytics initiatives for Provost priorities (e.g., student persistence/retention, time-to-degree, course demand forecasting, classroom utilization, etc.).
Build predictive and prescriptive models (e.g., risk scoring, enrollment forecasting, course section optimization) using R/Python; translate outputs into decision-ready visuals in Power BI.
Develop advanced semantic models to support executive dashboards and KPI scorecards with robust DAX measures.
Developing data products to support enterprise KPI tracking for strategic projects.
Lead initiatives to support self service analytics within the office of the provost to enhance operational efficiency.
Support IRSA’s goals of sourcing all key data from the data warehouse.