Top Data & Analytics Jobs in CO

The Senior Manager of Data Engineering will build a data platform, lead a team, and ensure data accessibility to support AI and business operations.

Lead data engineering engagements to design, build, and maintain ETL/ELT pipelines and cloud data architectures. Manage client accounts and mentor teams, leverage tools like DataStage, AWS/Redshift, DB2/SQL Server, GoldenGate, and BI/visualization platforms to deliver analytics, performance tuning, and scalable reporting solutions.

Design, implement, and maintain BI solutions and analytics to deliver client insights. Use tools like Oracle BI, QlikView, and Spotfire, analyze complex data sets, build data pipelines, collaborate with stakeholders, manage teams, and uphold professional and technical standards to improve business performance.

Lead BI initiatives and client accounts to deliver strategic insights. Design and implement BI and cloud analytics solutions, validate data integrity and compliance, optimize data utilization, mentor teams, manage project planning/budgeting, and drive continuous improvement.

Develop and maintain data contracts, metadata standards, AI-readiness scoring pipelines, and governance/compliance tooling. Build quality monitoring, semantic layer assets, and AI-augmented development workflows. Collaborate with data owners and platform teams to onboard assets, ensure data trust, and enable AI-driven analytics.

Build and maintain BI solutions: design ETL and pipelines, create dashboards and reports, automate large-scale data transfers, ensure data quality, and deliver actionable analyses to marketing stakeholders and senior leadership.

Lead Finance Data & Analytics to build trusted data sources, governance, and analytics for Finance and cross-functional stakeholders. Manage analysts, drive data strategy and Snowflake data models, produce insights via SQL and Tableau, and deploy AI solutions to optimize finance decision-making and operations.

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.

Design and build Toast’s enterprise analytics layer and AI-ready semantic layer in the data warehouse. Collaborate with domain teams and data engineering to implement hub-and-spoke architecture, define complex business logic in SQL, support scalability, partner with stakeholders, and provide technical mentorship.

Manage design and delivery of reusable, AI-ready data products for retail-banking portfolios. Develop interoperable data-engineering artifacts, enable self-service analytics, maintain data marketplace, oversee data policies, integrity, budgeting, stakeholder alignment, and lead cross-functional teams in a matrixed environment.

Design, harden, and scale Snowflake and AWS data platforms, build dimensional data models and resilient Airflow pipelines, optimize complex SQL, develop dbt semantic layers, deploy ML models in AWS, integrate AI/LLMs into workflows, and build data APIs (FastAPI/Flask) to enable enterprise analytics and operational ROI.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.

Partner with stakeholders to gather and document data requirements, translate needs into user stories and technical specs, perform SQL-based data analysis, source-to-target mapping, and validation, support data quality, lineage, and monitoring, serve as primary requirements contact, contribute to Agile ceremonies, assist change management and rollout, and maintain operational and client documentation.