Top Remote Analysis Reporting Jobs in Salt Lake City, UT

Own end-to-end analytics delivery for a client POD, translating business priorities into workplans, coordinating cross-functional teams, governing delivery and revenue KPIs, and managing risks through resolution. Perform hands-on data profiling, validation, reconciliation, exploratory analysis, automation, and quality reviews using SQL, Python, Databricks, and Excel. Create executive-ready KPI, revenue, and business-impact narratives, prioritize initiatives, support business cases, and identify opportunities for analytics automation and AI-enabled improvements.

Lead the technical direction, architecture, and roadmap for the company’s data platform. Design reliable large-scale pipelines, establish standards for modeling, testing, observability, and orchestration, and mentor data engineers. Partner with engineering, product, analytics, and business stakeholders to align infrastructure investments. Lead incident root-cause analysis, evaluate data technologies, and support scalable analytics, machine learning, and real-time processing capabilities.

Designs and operates scalable ETL/ELT pipelines, data models, schemas, and cloud data infrastructure supporting analytics, reporting, and product features. Responsibilities include monitoring pipeline health, resolving data quality issues, improving performance and cost efficiency, documenting systems, collaborating with engineering and analytics teams, and participating in production incident response.

Own the digital measurement ecosystem across websites, quote engines, customer portals, and account applications. Lead Google Tag Manager tracking frameworks, data-layer standards, Google Analytics 4 configuration, conversion events, attribution, funnel analysis, experimentation measurement, data-quality audits, and analytics governance. Partner with Marketing, Product, Engineering, and Data teams to translate customer behavior into actionable insights that improve growth, conversion, and customer experience.

Design and operate scalable, cloud-native data pipelines and orchestration systems for imaging, biomarker, and healthcare data. Build Databricks and distributed processing workflows, integrate DICOM data into data lakes, and implement validation, observability, monitoring, and fault tolerance. Collaborate with data science, AI, R&D, product, and data management teams to deliver secure, compliant, reliable data for analytics and machine learning.

Design and build petabyte-scale multimodal data pipelines and infrastructure (text, audio, images, video). Own and maintain systems like Spark, Ray, and vector databases, partner with pre/post-training teams to improve data recipes through experimentation, and support large-scale dataset storage and processing for AI model training.

Own and maintain the companys data infrastructure and pipelines. Design, build, and monitor ETL/ELT workflows and data architecture; integrate SaaS sources; enforce data quality, standards, and governance; partner with stakeholders to deliver analytics-ready data and meet data availability SLAs.

Analyzes, validates, and prepares distribution data; develops dashboards, reports, and visualizations; supports warehouse management systems, labor management, configuration, testing, and continuous improvement. Partners with Distribution, IT, process teams, engineers, and vendors to provide business intelligence, troubleshoot systems, communicate data insights, and support operational and strategic decisions.

Designs and operates an AWS-native lakehouse supporting analytics, reporting, visualization, and AI/ML. Builds batch and streaming ingestion pipelines using Python and PySpark, Apache Iceberg data structures, governance and metadata services, quality controls, security, observability, and CI/CD automation. Optimizes performance, scalability, reliability, and cost while collaborating with cross-functional technical teams and documenting architecture, operations, and secure configurations.

Administers, designs, secures, monitors, and optimizes large-scale client/server databases. Responsibilities include database programming, performance tuning, backup and disaster recovery, access control, auditing, documentation, systems integration, and advising users. The role requires supporting database projects in large organizations, working across operating systems and cloud platforms, and maintaining sensitive data security. A Secret clearance and DoD IAT Level II certification are required.

Analyzes complex business processes, data requirements, and information systems supporting the Defense Logistics Agency. Applies DoD Business Enterprise Architecture, data modeling, enterprise architecture, systems integration, and process analysis expertise to improve data quality, interoperability, modernization, and enterprise decision-making. This fully remote role requires Secret clearance and supports AMPS program initiatives.

Lead enterprise data architecture for Privia Health’s Snowflake platform, defining scalable modeling, integration, governance, security, and optimization standards. Design Medallion Architecture layers and healthcare data schemas spanning EMRs, claims, eligibility, and value-based care data. Establish dbt, Python, testing, orchestration, and CI/CD best practices; enforce HIPAA, PHI/PII masking, access controls, lineage, and cataloging. Provide technical leadership, design reviews, mentorship, and cross-functional guidance to engineering, analytics, clinical, and product stakeholders.