Top Remote Data & Analytics Jobs in Salt Lake City, UT

Own enterprise analytics audits, implementations, data quality, attribution, segmentation, SQL analysis, BI dashboards, experimentation measurement, and client reporting. Serve as the senior analytics partner for major accounts, present insights to executives, train client and internal teams, and help define analytics and experimentation services. The role requires hands-on Adobe expertise, autonomous prioritization, technical collaboration, and the ability to connect organic and AI search performance to pipeline and revenue.

Conduct AI-powered web research, scraping, market analysis, and lead generation to identify clients, partners, sponsors, investors, and collaborators. Build and maintain intelligence databases, automate research workflows, verify and enrich data, analyze unstructured information, prioritize opportunities, and present actionable recommendations to leadership.

Clean, standardize, enrich, and import product data into the PIM while maintaining data integrity and governance standards. Oversee bulk ingestion processes, leverage AI and automation, support data model improvements, resolve product listing issues, and contribute to data hygiene and workflow modernization. The role also involves collaborating with client-facing teams, documenting processes, proofreading product data, communicating progress, and adapting to changing priorities.

Design, build, deploy, and operationalize scalable data engineering solutions for customers. Responsibilities include developing pipelines, transforming and cleansing data, analyzing sources, implementing governance, security, and quality practices, testing data movement and transformation code, resolving defects and incidents, and advising customers on technical decisions. The role also supports AI, machine learning, business intelligence, and data product adoption while collaborating across teams and educating end users.

Own end-to-end analytics across marketing, revenue, product, and partnerships. Build reliable data models and semantic layers in a lakehouse, maintain dashboards and monitoring, investigate anomalies, conduct experimentation, and translate complex analyses into recommendations for senior stakeholders. The role requires advanced SQL, Python, data modeling, stakeholder communication, autonomy, and mentoring, with responsibility for improving data quality and building analytical standards in a high-growth startup.

Monitor news, media, social platforms, and events; prepare data for media analysis and reports; create Excel pivot tables, charts, and visualizations; write analytical insights; support research projects; and validate proprietary reputation-risk and stakeholder-view scoring. The intern will help deliver timely client alerts, briefings, and longer-term reports while collaborating with analysts and interpreting trends across business, culture, and politics.

Provides data analytics and business intelligence support for government customers. Responsibilities include gathering requirements, analyzing and transforming enterprise data, designing data models, developing dashboards and visualizations, documenting governance processes, improving workflows, and training users. The role requires government acquisition, finance, or financial management experience, preferably within DoD or Air Force systems, and supports financial office operations.

Conduct individual and institutional prospect research, donor profiling, pipeline qualification, due diligence, and risk assessments. Synthesize financial, philanthropic, and relationship information into briefings, event snapshots, leadership summaries, and board bios. Proactively identify new donor prospects, monitor wealth and philanthropic trends, and support board and geographic expansion initiatives. Train Development staff on research tools, establish service protocols, and manage research requests independently while protecting confidential information.

Own GTM reporting and analytics across Salesforce, warehouse systems, Tableau, and Excel. Build trusted dashboards, define metrics, investigate data quality issues, and lead analysis for pipeline, forecasting, territory design, capacity planning, productivity, and resource allocation. Partner with GTM, CRM, Data, and Systems stakeholders to improve reporting architecture and support leadership decisions. Use AI tools to automate analysis and develop internal analytics workflows.

Build and own the data platform backbone: design ingestion patterns, Snowflake warehouses, governance, and freshness strategy. Implement reliable batch and streaming pipelines, data quality, observability, and onboarding processes. Lead legacy migrations, create data contracts and SLAs, and apply AI-native tooling to automate debugging, documentation, and operational workflows while partnering with Analytics, Engineering, and vendors.