Top Analysis Reporting Jobs in Ogden, UT

Develop and own healthcare-related data analyses, financial models, databases, and data resources. Write Python and SQL code, validate results, perform data quality audits, identify anomalies, and maintain data integrity. Create reports, presentations, diagrams, and engineering requirements documents, while partnering with strategy leads and cross-functional stakeholders to design data-informed technology solutions. Support client projects, communicate findings, and ensure accurate, compliant deliverables.

Build and maintain ETL and data pipelines using Python, PySpark, and AWS services. Orchestrate workflows, develop event-driven integrations, optimize data storage and queries, process API and JSON data, and implement data quality monitoring. Support CI/CD, production operations, cloud migration, data lake and lakehouse initiatives, and near-real-time systems while collaborating with stakeholders to deliver technical solutions.

Builds, operates, and owns enterprise data warehouse pipelines and models on Databricks. Develops Delta Lake batch and streaming pipelines across Bronze, Silver, and Gold layers; implements data quality, reconciliation, observability, governance, and performance improvements. The role owns assigned data domains, supports event-driven ingestion, documents architecture and runbooks, responds to incidents, collaborates with QA and governance teams, and mentors data engineers.

Lead the Ads Signals & Measurement data engineering team across conversion and attribution, measurement foundations, audience onboarding, and identity. Set cross-organizational technical direction, resolve scalable data architecture decisions, mentor engineers, and partner on platform-wide initiatives. The role requires expertise in modern data stacks, advertising technology data flows, privacy and governance, distributed systems, and emerging AI technologies.

Own trade performance reporting, dashboards, scorecards, promotional ROI analysis, range review support, category insights, and sales projections for major retail customers. The role turns sales and shopper data into commercial recommendations, supports retailer presentations and new product launches, and collaborates with Sales, Marketing, Supply Chain, Demand Planning, and Finance. It requires strong Excel and presentation skills, commercial curiosity, attention to detail, clear communication, and the ability to manage multiple priorities.

Organize and curate large volumes of raw information: extract key points from transcripts, maintain clean spreadsheets, curate links/resources, tag and categorize content, and follow or propose systems for information structure. Part-time remote role with initial 10 hours/week and potential to grow.

Own Fi’s data platform and analytics roadmap, building event-driven pipelines, warehouse models, self-serve BI, and experimentation capabilities. Lead and develop a team of four analysts while partnering with Finance, Product, and Hardware on forecasting, unit economics, device analytics, retention, and board reporting. Serve as a strategic data leader in a fast-growing Series B startup.

Own and scale client-facing data transformation pipelines for financial and operational data. Build reliable analytical models, data integrity tests, and integrations across diverse sources. Partner with Customer Success and Engineering to troubleshoot data issues, optimize critical pipelines, establish engineering standards, and improve developer experience. Use dbt, SQL, Python, BigQuery, and AI-enabled workflows to deliver performant, well-documented FP&A data products while mentoring teammates and contributing to hiring and onboarding.

Build and maintain ETL/ELT pipelines, ingest and transform structured and unstructured data, integrate APIs and external sources, improve data quality and monitoring, support dashboards and ML pipelines, optimize warehouse and cloud performance, and contribute to data governance and documentation.

Design, develop, and optimize enterprise-scale data platforms, pipelines, data lakes, warehouses, and analytical datasets on Azure and Snowflake. Build ETL/ELT processes using ADF, Databricks, PySpark, SQL, Python, and Snowflake. Manage data models, governance, security, quality, CI/CD, cloud migrations, and performance optimization. Collaborate with stakeholders, troubleshoot production issues, document solutions, and support Agile delivery.