Top Data & Analytics Jobs in Provo, UT

Design and govern end-to-end data architecture for an integrated supply-chain e-commerce platform: create data models, build scalable ETL/ELT pipelines, ensure GDPR-compliant data governance, enable real-time analytics, optimize databases, plan retention/archival, and prepare data for LLM fine-tuning and RAG use cases.

Provides remote and in-country monitoring, evaluation, accountability, and learning technical assistance across development and emergency programs. Responsibilities include designing MEAL systems, indicators, data collection tools, budgets, evaluations, dashboards, and learning agendas; supporting donor proposals; deploying to humanitarian responses; training and mentoring staff and partners; generating evidence; and engaging donors, governments, and peer organizations. Requires strong analytical, strategic, facilitation, relationship-management, and communication skills, with up to 40% travel.

Own Bridge’s data function by building reliable pipelines, ETL orchestration, dbt models, marts, data products, dashboards, alerts, and self-service analytics. Investigate ambiguous business questions, improve data quality, structure business context for AI systems, and develop AI-powered tools and evaluations. The role also requires documentation, testing, code review, training, and cross-functional support.

Design, develop, and maintain Customer Data Platform solutions and data pipelines to create unified customer profiles, manage identity resolution, enable audience segmentation and activation, ensure data quality and governance, and support integrations with marketing, CRM, and cloud data systems.

Designs, builds, and manages cloud-based data systems, including pipelines, data lakes, warehouses, lakehouses, databases, and ETL processes. Develops optimized Python and SQL queries, improves workflow performance, and supports data movement between on-premises and cloud environments. Collaborates with leadership, analysts, research teams, and other departments to define requirements and reporting needs. Applies data governance, access controls, security, compliance, troubleshooting, and system support practices.

Provides public health research and evaluation support through qualitative, quantitative, and mixed-methods data analysis. Produces reports, interprets results, evaluates program implementation and outcomes, recommends improvements, and provides technical assistance to government clients and research recipients. The role also requires communicating findings to senior officials, managing administrative research systems, using data and reporting platforms, and following government research procedures.

Designs and builds modern data applications, pipelines, transformations, enrichment processes, provisioning layers, and interfaces supporting clinical and operational healthcare processes. Analyzes clinical data to identify trends, collaborates with Product, Platform, and Architecture teams, mentors junior data engineers, and evaluates emerging technologies. The role emphasizes cloud computing, big data, data science, modern development frameworks, source control, documentation, and repeatable engineering practices.

Leads advanced analytics initiatives supporting sales, marketing, and operations strategy. Develops statistical and predictive models, dashboards, KPI reporting, and customer analyses using large datasets. Partners with stakeholders and data engineering teams to translate business questions into actionable insights, communicates findings to executives, and mentors junior analysts.

Lead analytical support for performance marketing by evaluating CAC, ROAS, LTV, conversion, retention, and acquisition efficiency. Conduct deep-dive analyses, experimentation, incrementality studies, and marketing measurement using SQL, Python, and visualization tools. Build scalable reporting frameworks, improve data quality, communicate insights to senior stakeholders, influence channel and budget decisions, and mentor junior analysts.

Architects FHIR-compliant clinical data models and develops harmonization, enrichment, and validation strategies across EHR, HIE, and claims data. Maintains clinical ontologies and value sets, ensures data accuracy and longitudinal integrity, and documents technical requirements for engineering teams and stakeholders. The role requires advanced Python and SQL skills, healthcare interoperability expertise, and experience with clinical informatics or data integration.