Top Remote Senior Level Data Engineering Jobs in CO

Own and maintain the Kepler consumer transactions feed end-to-end: ensure data accuracy, refine methodologies, implement QA frameworks, prototype enhancements, use SQL/Python/PySpark and AI tooling to automate workflows, and collaborate cross-functionally to resolve high-complexity issues for clients.

Lead design and development of web UI and REST middleware within an Agile team. Define requirements and acceptance criteria, implement Java/Spring and Angular solutions, build CI/CD pipelines, work with Product Owner and testers, and produce/update design documentation.

The Senior Data Engineer will maintain and improve data infrastructure, design ETL processes, and create high-performance pipelines for analytics and AI initiatives using SQL and Python in cloud environments.

Lead architecture and execution of Grafana's marketing data stack and analytics practice. Build forecasting, predictive, and causal models, design BigQuery schemas, deploy agentic AI and automated pipelines, partner with GTM leadership, and deliver executive-grade insights to drive demand generation and ROI.

Restructure and maintain Airtable relational architecture for fertility industry data, implement automations and integrations (Zapier, Softr), enforce data governance and permissions, build dashboards and reports, execute data acquisition and enrichment to scale the database, conduct audits, document SOPs, and support onboarding and system monitoring.

The role involves driving product strategy for data infrastructure, leading cross-functional teams, and implementing MLOps practices for data engineering solutions.

Design and deliver Databricks-centric data architectures, lead pre-sales and billable engagements, build end-to-end data engineering pipelines for AI/ML and BI, mentor teams, ensure data governance/security/quality, and resolve data system issues while producing solution documentation and presentations.

Support P&C actuarial and data modernization by performing pricing, reserving, forecasting, and portfolio analyses; design and implement DWH solutions; develop data models; conduct experience and trend studies; support rate filings and regulatory submissions; build dashboards and reports; migrate actuarial data from legacy to cloud platforms; collaborate with actuarial, data engineering, and business stakeholders to ensure data quality and scalable analytics.

Own end-to-end client data migrations: reverse-engineer legacy ETL, design and build Airflow DAGs and Spark jobs, validate and reconcile data at scale, document architecture and decisions, and coordinate cross-functional teams through go-live and hypercare.

The Senior Data Engineer will develop data engineering solutions, manage ETL workflows, and establish a new data practice while collaborating with stakeholders.