Top Data & Analytics Jobs in Denver & Boulder, CO

Own the data foundation for Gusto’s Customer Experience organization, including pipelines, data models, dashboards, monitoring, and reporting. Partner with CX leaders and data teams to define metrics, investigate customer outcomes, apply statistical methods and AI-driven anomaly detection, and improve data quality and governance. Build scalable self-service insights, communicate findings to technical and non-technical stakeholders, and mentor data practitioners while independently driving high-impact projects.

Lead marketplace analytics for Affirm’s two-sided ecosystem by optimizing monetization, supply, demand, pricing, profitability, and user experience. Build KPI dashboards, analyze marketplace and affiliate performance, conduct experiments, evaluate incentives and placement, and perform loan-level profitability analyses. Partner cross-functionally with Product, Engineering, Sales, Client Success, and Marketing to improve merchant value, consumer engagement, conversion, and sustainable GMV growth.

Build Affirm’s narrative intelligence function by analyzing audience, behavioral, brand, media, survey, and business data. Develop narrative measurement frameworks, dashboards, analytical standards, and feedback loops to assess how effectively communications resonate. Design rigorous research studies, integrate qualitative and quantitative evidence, identify meaningful patterns, and translate findings into positioning, messaging, campaign, content, and communications strategy. Partner across analytics, research, marketing, creative, and communications teams to turn complex evidence into actionable decisions.

Design and develop data pipelines, integrations, transformations, and infrastructure across AWS, Snowflake, Airflow, and MySQL. Troubleshoot warehouse issues, validate data quality, improve pipeline reliability, and translate business needs into data engineering solutions. Interpret technical findings for client recommendations, manage workstreams, review junior team members’ work, and provide technical guidance across managed services engagements.

Lead Toast’s global People Analytics function across data engineering, analytics, data science, and employee listening. Set the people data and reporting strategy, establish trusted metrics and governance, partner with executives on workforce decisions, measure People program impact with Finance, and build scalable self-service analytics. Manage a distributed US and India team, oversee executive and board-level workforce analysis, and collaborate with privacy, legal, People technology, AI, and data engineering teams.

Leads client analytics across the full sales cycle, designing measurement strategies, experiments, incrementality, marketing mix modeling, and attribution solutions. Partners with revenue teams and C-suite clients to translate data into commercial outcomes, support renewals and expansions, and develop scalable insights. Requires mentoring analytics staff, presenting recommendations, managing complex engagements, and applying strong technical skills in SQL, Python, Databricks, and Git/GitHub.

Performs data profiling, quality analysis, governance, metadata and lineage management, and Master Data Management support. Collaborates with data owners, stewards, business stakeholders, and technical teams to resolve issues and improve governance processes. Maintains glossaries, dictionaries, controls, metrics, and reports; supports enterprise data initiatives, communications, training, and stakeholder adoption. Provides guidance to less experienced analysts while applying governance standards and documenting business requirements.

Lead enterprise data architecture across warehouses, data lakes, downstream applications, and AI workloads. Design data models, Medallion Architecture, ELT standards, semantic layers, APIs, access controls, and reusable datasets. Partner with business and BI teams to drive adoption, conduct architecture reviews, establish platform standards, and mentor data and analytics engineers. The role requires deep Snowflake, dbt, data modeling, pipeline, and semantic-layer expertise, with experience in AI data patterns and cloud infrastructure preferred.

Conduct qualitative and quantitative consumer research to identify needs, trends, and product opportunities. Analyze consumer feedback, translate findings into actionable recommendations, and support product roadmaps, positioning, experience design, and go-to-market planning. Collaborate with Product Development, Marketing, and Design teams while managing research partners and multiple projects.

Leads the architecture, administration, engineering, and strategic evolution of enterprise Hadoop-based data platforms. Owns cluster lifecycle, scalability, reliability, security, disaster recovery, monitoring, optimization, upgrades, and operational standards. Troubleshoots distributed systems, supports data ingestion and governance, guides hybrid cloud strategies, documents platform operations, and mentors engineering teams. The role also develops data views, exports, and automated processing while collaborating with data engineering, analytics, security, and infrastructure teams.

Leads enterprise-scale data architecture across batch, streaming, warehouse, lakehouse, transactional, AI, and vector-store use cases. Establishes data quality, governance, lineage, observability, access-control, and reliability standards. Defines AI-enabled data engineering patterns, mentors engineers, resolves complex architecture issues, and influences cross-functional roadmaps. Requires hands-on technical leadership and 15+ years of software, data engineering, or architecture experience.