Top Data & Analytics Jobs in CO

Design and maintain analytical data models, transformation frameworks, data-quality checks, semantic definitions, and metric consistency across analytics and customer-facing products. Partner with engineering, product, and analytics teams to document data, improve lineage, and enable trustworthy self-service data usage. The role requires advanced SQL, analytics engineering, dimensional modeling, testing, and collaborative translation of business concepts into precise data definitions.

Lead the architecture, development, and scaling of data pipelines and infrastructure for a customer-facing Data Lake platform. Build ETL and ingestion systems using GCP, Debezium, Pub/Sub, Dataflow, BigQuery, Python, Golang, and SQL. Establish engineering standards, deliver strategic projects, mentor engineers, influence cross-functional technical decisions, optimize data services, and shape the platform roadmap.

Leads broadband business intelligence initiatives by analyzing complex datasets, developing cross-functional dashboards and reporting structures, guiding data strategy, and delivering customer and business performance insights. Presents advanced analyses and strategic recommendations to senior leadership. Requires expertise in SQL, ETL, data visualization, reporting design, and analytical modeling, with collaboration across technology, finance, marketing, telecom, supply chain, and procurement teams. This is a hybrid role requiring at least three days per week in the office.

Lead the architecture and development of Vercel’s next-generation data platform, supporting batch and real-time integrations, analytics, data warehousing, and AI/ML workloads. Design scalable systems using Kafka, ClickHouse, Tinybird, and Snowflake; establish data governance and security standards; guide architectural decisions and roadmaps; collaborate with engineering, product, security, compliance, and leadership teams; write production code; and mentor engineers.

Develop and optimize cloud-based data pipelines for analytics, machine learning, LLM feature stores, and AI applications. Build AI agents, integrate large language models and vector datasets, implement monitoring and self-healing workflows, and establish data observability for freshness, lineage, and performance. The role also structures semantic data layers, improves resource utilization and cloud costs, troubleshoots distributed platforms, and collaborates across teams to align data infrastructure with business needs.

Leads the enterprise data platform strategy, architecture, governance, and evolution. Manages a central data team and enables federated self-service analytics across business functions. Builds AI-ready data pipelines, RAG and Graph RAG architectures, custom data applications, observability, cost optimization, and AIOps capabilities. Requires hands-on expertise with Snowflake, dbt, modern ETL, Python, SQL, CI/CD, and Data Mesh architectures, along with 5+ years leading technical data teams.

Lead complex data analyses, develop statistical models, write advanced SQL, build data models and dashboards, and establish technical standards for analytics. Mentor analysts, troubleshoot data quality and modeling challenges, partner with data engineering, translate ambiguous business questions into rigorous analyses, and communicate findings to senior stakeholders. Own the analytics function’s technical roadmap while ensuring data privacy and security practices.

Build and maintain Engine X performance dashboards, reporting frameworks, data models, and complex SQL analyses using Snowflake. Track card, booking, rewards, spending, and retention metrics; investigate anomalies; support A/B tests; document metric definitions; and communicate findings to product, finance, and leadership. Collaborate with analytics and data engineering teams to validate pipelines and improve data quality.

Leads analytics for Pricing and Supply, managing a team of approximately eight analysts. Partners with cross-functional leaders to prioritize analytical work, build dashboards and decision frameworks, improve metric quality, and generate insights into pricing, supplier coverage, marketplace performance, conversion, margin, and customer behavior. Coaches analysts, establishes scalable analytics processes, and collaborates with data engineering teams to improve data models, tooling, and self-service capabilities.

Leads a 15+ person analytics organization supporting Growth, Sales, Marketing, and Finance. Owns the analytics strategy, operating model, metric governance, executive reporting, forecasting, experimentation, customer and revenue insights, and data foundation improvements. Partners with senior commercial and financial leaders to translate complex data into strategic recommendations and builds scalable processes, systems, and talent development programs.

Own product analytics and customer success data domains by building governed models for product usage, feature adoption, customer health, onboarding, renewals, churn, expansion, and net revenue retention. Partner with Product, Customer Success, RevOps, Finance, and analysts to create semantic models, metric definitions, instrumentation, documentation, alerting, and self-service tools. Use dbt, Snowflake, Omni, Hex, and AI-assisted development to turn ambiguous stakeholder questions into durable data products.

Build and govern Ibotta’s foundational data platform using Python, SQL, Terraform, Databricks, AWS, and Spark. Develop infrastructure provisioning, access controls, governance automation, self-service tooling, and scalable data pipelines. Support reliability through incident resolution, root cause analysis, on-call participation, and platform improvements. The role requires three years of software or data engineering experience and is hybrid in Denver.