Senior Business Intelligence & Analytics Engineer

Upland Capital Group•Dallas, TX

22h

About The Position

Upland 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.

Requirements

5+ years of professional experience in analytics engineering, data engineering, data platform development, or a related field.
Bachelor's degree in a technical or quantitative field (or equivalent experience).
Advanced proficiency in SQL and data modeling.
Strong expertise with dbt and Snowflake; working knowledge of Python.
Advanced experience with a modern BI platform; hands-on Sigma Computing experience strongly preferred.
Demonstrated experience leading complex analytics initiatives with solid problem-solving skills.
Strong communication skills with both technical and non-technical teammates.

Nice To Haves

Insurance industry experience preferred but not required.

Responsibilities

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.
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.