Top Data & Analytics Jobs in CO

Serve as the primary finance contact for IT departments, supporting financial planning, analysis, and operational queries while developing frameworks for performance assessment and creating financial presentations for management.

The Ticketing Insights Analyst II analyzes complex ticketing data to improve operational efficiency and customer experience through automation and data storytelling while collaborating with various teams to drive insights.

Analyze transactional and operational payments data to monitor performance, detect risk and fraud, and improve collections. Build, validate, and automate daily/weekly/monthly reports and alerts, consolidate data sources, deliver insights to stakeholders, and support special analytics projects to drive operational efficiency.

Lead advanced analytics for countrywide insurance product programs: build dashboards and monitoring frameworks, conduct deep-dive analyses and predictive modeling, identify systemic process and data gaps, partner with product and cross-functional teams, and influence strategic decisions to improve growth, retention, and profitability.

Lead the design and operation of automated compliance monitoring for consumer lending: translate regulations into rule-based data checks, own exam and audit data requests, triage exceptions, drive automation, steward compliance data, and provide technical mentorship to a supporting analyst. Produce audit-ready, reproducible evidence for regulators, bank partners, auditors, and senior leadership.

Design and implement enterprise analytics tracking across web, mobile, and SPAs using Tealium and other TMSs. Maintain data layers and SDRs, configure tags and events, validate data integrity, collaborate with engineering teams, mentor junior staff, produce technical documentation, and support presales and thought leadership activities.

Build and operate an enterprise Databricks lakehouse: design and maintain Bronze and Silver ingestion/transformation pipelines (batch/stream/CDC), implement Unity Catalog and secure platform constructs, create CI/CD for data assets, enforce data classification and quality, and collaborate with domain teams to enable governed data for analytics.

Own and design the Databricks Gold and enterprise semantic layer: implement governed facts, dimensions, KPIs, and semantic models. Translate business KPI definitions into auditable transformation logic, enforce governance promotion paths, review models for correctness, coach domain teams, and ensure traceability, documentation, and compliance-aware data exposures for BI and self-service analytics.

Lead KPI reporting, funnel analysis, forecasting, and business diagnostics for Enterprise Growth across Coursera + Udemy. Build unified definitions and durable self-serve reports, support experiments and inside-sales/outsourced partner evaluation, and provide analytical inputs for target setting and prioritization to drive growth and conversion improvements.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Lead technical design and architecture for analytics engineering: build and govern the semantic/metrics layer, optimize dbt and Snowflake for performance and AI use cases, mentor engineers, partner with Data Science and Engineering, drive data quality, CI/CD, observability, and deployment of third-party data and emerging tooling to support analytics, ML, and agent-based products.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Lead design and scaling of the data platform and analytics pipelines. Build and maintain ETL/ELT workflows, integrations, serverless data services, and reliable data models. Mentor teammates, improve automation, observability, and data governance to support analytics and operational insights.

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.