Top Data Analyst Jobs in Denver & Boulder, CO

Lead monitoring and optimization of programmatic ad campaigns using real-time and historical data. Diagnose performance issues, design A/B and multivariate experiments, partner with AdOps and Data Science to operationalize ML-driven solutions, and drive automation of campaign decisioning to scale revenue and efficiency.

Build and maintain dbt models, write SQL to investigate and validate data, implement data quality checks, document lineage and metrics, resolve production issues (including on-call), and partner with analysts and business teams to deliver production-ready data products using modern warehouse tooling and AI-assisted frameworks.

The Data Analyst II analyzes data using SQL, Python, and R to provide actionable insights, improve processes, and support decision-making across teams. Responsibilities include developing forecasts, liaising with stakeholders, and presenting findings to executives.

As a Data Analyst II, you will enhance marketing strategies by auditing current data processes, creating dashboard reports, and conducting A/B tests with statistical validation to drive customer engagement and growth.

Lead data analysis and reporting for the Trading team, build and maintain dashboards and governed analytics, deliver quantitative research, mentor juniors, and present insights to stakeholders to support decision-making and next-gen trading platform development.

As a Staff Data Analyst, you'll drive data analysis, build business intelligence tools, and collaborate across teams to optimize Upstart's servicing strategy, while mentoring junior analysts.

The Lead Data Analyst (Network) drives data-driven initiatives, dissects datasets, and provides actionable insights to enhance business performance and network efficiency.

Lead Data Analyst responsible for advanced analytics, real-time dashboards, capacity modeling, and network performance insights. Collaborates with stakeholders to identify inefficiencies, run tests and pilots, and deliver actionable recommendations to improve service provider performance and network operations.

The Data Analyst in Revenue Operations will analyze sales data, build models, and create reports using SQL, Excel, and BI tools to empower business decisions.

Own BI analytics using a modern data stack to generate insights, build dashboards and self-serve tools, partner with stakeholders, and deploy AI-driven reporting and natural-language query solutions.

As a Principal Analyst in Growth Marketing, you will lead analytics for acquisition channels, applying advanced analytical techniques to drive business growth and improve marketing performance while collaborating across teams.

The Senior Data Analyst will perform hands-on analytical work using SQL, design A/B tests, develop dashboards, and partner cross-functionally to drive data-informed decision-making across various teams.

The Lead GTM Data Operations Analyst will operate and extend AI-driven data quality pipelines, optimize agent outputs, and monitor offshore resolution teams, ultimately improving data accuracy and management in a dynamic, evolving environment.

The Senior Customer Lifecycle Analyst leads data-driven projects focusing on customer retention, engagement, and lifetime value, leveraging advanced analytics and visualization tools to provide business insights and recommendations.

The Data Strategy & Sourcing Analyst transforms product data into a strategic asset, ensuring data integrity and driving cost savings through sourcing. Responsibilities include establishing a Single Source of Truth, conducting data analysis, and collaborating with teams for financial impact. The role requires strong analytical skills, proficiency in SQL, and experience with data management tools.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Prepare, validate, and maintain member data lists in Snowflake for email, SMS, and print; build automated data quality checks; manage suppression and PHI-related compliance; document transformations; partner with Marketing Operations and centralized Data to resolve issues and support audits and ad-hoc reporting.

Design and implement data processes for marketing campaigns (data cleaning, mapping, ETL, validation). Support Salesforce Marketing Cloud data architecture, enforce governance and compliance, build queries and reports, track KPIs, collaborate with marketing/product/sales/vendors, and optimize multi-channel campaign execution to drive growth, retention, and engagement.

Lead and enhance Stripe's analytics infrastructure by setting standards, solving complex data challenges, improving data quality, and driving technical vision across teams.

Support financial data processing and reporting using SQL, SSRS, and Power BI; design BI reports and dashboards; analyze and automate business systems; write specifications and technical documentation; collaborate across finance, IT, operations, and legal to improve and scale processes.

Analyze, integrate, clean, and model operational and technical data to produce dashboards, reports, and forecasts. Identify trends, lifecycle/status, risks, and noncompliant assets; support automation, data quality improvements, and decision-making across engineering and operations teams.

Own and build the support reporting layer: ticket volume, SLA, resolution times, CSAT/CES/sentiment, and capacity. Produce dashboards and analyses for leadership and engineering, maintain data quality and governance, prioritize issues using multi-signal models, and surface Voice of Customer trends to close the loop with Product and GTM.

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

Perform end-to-end data analysis and transformation for large-scale P&C insurance datasets. Develop source-to-target mappings, validate and profile data, optimize complex SQL queries, and collaborate with business SMEs and technical teams to ensure data quality, standardization, and accurate technical documentation.

Lead analytics work across revenue, product, customer, and operations by building dashboards, conducting deep-dive analyses, defining metrics and reporting standards, validating data quality with Data Engineering, and using AI tools to automate reporting and accelerate insights. Communicate findings to technical and non-technical stakeholders and proactively surface trends and opportunities.