Senior Business Intelligence & Analytics Engineer
Listed on 2026-09-27
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IT/Tech
Data Engineering
Senior Business Intelligence & Analytics Engineer
Upland Capital Group, Inc. is an AM Best rated “A-” VIII specialty property/casualty insurer headquartered in Dallas, Texas. Through its wholly owned insurance carrier, Upland Specialty Insurance Company, the company markets, underwrites and services specialty insurance products in select markets to include excess transportation, construction casualty, excess casualty, primary general liability, excess public entity, professional liability errors and omissions as well as excess cyber liability.
We focus on “old school” underwriting as a craft, add “new school” analytics and technology, and encourage a gritty, growth mindset among people called “we entrepreneurs.”
As an Excess and Surplus (E&S) carrier, we face unique and interesting challenges every day. We are seeking a Senior Business Intelligence & Analytics Engineer to join our amazing team.
Primary FunctionUpland Capital Group is seeking a Senior Business Intelligence & Analytics Engineer to be a technical expert within our growing Data organization. This is a high-impact, hands-on role responsible for continued building and maintaining of our data platform, architecting scalable, well-governed data models, and delivering analytics solutions that directly influence underwriting, claims, and executive decision-making.
You will provide technical mentorship, guide best practices across SQL, dbt, and BI development, and act as a key partner to cross-functional leaders. Senior Engineers at Upland are expected to operate with significant autonomy-owning complex projects end-to-end, elevating data quality standards, and contributing to the long-term design of our data platform.
The ideal candidate- Operates with mature technical judgment and strong business acumen
- Leads others through influence, mentorship, and exceptional communication
- Thrives in a fast-paced, evolving environment
- Think in systems - comfortable owning platform architecture, not just individual models
- Drives innovation, standardization, and continuous improvement
- Sets a high bar for accuracy, documentation, and data governance
- Design, develop, and maintain core layers of the data platform, including ingestion, transformation, and semantic layers.
- Support the reliability and timeliness of recurring reporting cycles that depend on the data platform
- Design, build, and optimize scalable dbt models, data marts, and analytics layers
- Write, optimize, and review complex SQL with a focus on performance, reliability, and maintainability
- Build and maintain Sigma data models, workbooks, and self-service analytics solutions
- Apply engineering rigor - testing, CI/CD, version control - to analytics development
- Translate complex business requirements into well-designed analytical solutions
- Lead code reviews, enforce modeling and naming standards, and mentor engineers and analysts on the team
- Proactively identify and resolve data quality, modeling, and pipeline performance issues
- Contribute to analytics engineering standards, documentation, and long-term architecture decisions
- Additional responsibilities as needed
- Troubleshoot and resolve platform and pipeline issues affecting downstream consumers
- Follow internal data governance, documentation, and security standards
- Represent the team in strategic discussions related to process improvements
- Participate in team retrospectives and process improvements
- Keep documentation current as dashboards and pipelines evolve
- Drive cross-functional initiatives to expand the company’s data maturity
- Stay updated on tools used by the team (e.g., dbt, Sigma, Snowflake, Azure)
- Contribute to a team culture that values clarity, curiosity, and follow-through
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