Top Hybrid Data & Analytics Jobs in CO

Validate and review CO APCD-derived data products using SQL and visualization tools, perform output comparisons and project-level analyses, follow quality control standards, document findings, and communicate results to technical and non-technical stakeholders while supporting continuous improvement of data QA processes.

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.

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.

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.

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.

Build and support enterprise data ingestion, transformation, modeling, and integration solutions using Microsoft Fabric and Azure data services. Develop batch, API, file, database, and event-driven pipelines; create dimensional and curated data models; write and optimize SQL; resolve data-quality and pipeline issues; and support production workloads. Collaborate in Agile engineering processes using GitHub, Azure DevOps, CI/CD, code reviews, and reusable development standards.

Leads data strategy for MetLife’s Group Benefits business by connecting business and Data & Analytics teams, establishing shared definitions, resolving ownership gaps, and improving governance and quality. The role leads Data Councils, supports Agile Release Trains, removes data-related blockers, and strengthens data foundations for decision-making, service delivery, analytics, and AI initiatives.

Owns go-to-market funnel reporting and analytics from lead generation through pipeline, bookings, and ARR. The role analyzes conversion, pipeline quality, CAC, LTV, marketing ROI, and sales efficiency across segments and channels. It builds dashboards, forecasts, and executive insights while partnering with Marketing, Sales, Revenue Operations, and Finance on attribution, data integrity, budgeting, and investment decisions.