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# Senior Analytics Engineer

- **Company:** BetterUp, Inc.
- **Location:** Austin, TX, United States
- **Experience:** Expert
- **Salary:** $175,000.0 - $220,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Code Review, Continuous Integration, Data Validation, Information Engineering, Extract Transform Load (ETL), Data Security, Data Warehousing, Cursor, Database Development, Federal Information Processing Standards (FIPS), Software Engineering, SQL Databases, Sql Optimization, Large Language Models, Claude Code, Snowflake, Looker Analytics, Software Version Control, Data Pipelines
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-analytics-engineer-austin-tx--0564513f-217d-41c1-9d77-8364b749f895

## About the Role

Coaching, Business Intelligence, Startup, Data Warehousing, Data Modeling, Business Solutions, Looker, Analysis Skills, Service Delivery, Leadership, * Minimum 5+ years of relevant experience in data engineering and/or analytics engineering

 * Advanced SQL skills with 5+ years of deep experience with Snowflake or similar DB
 * Expertise with data modeling and ETL/ELT (dbt preferred, pipeline development a plus)
 * Seasoned developer (5+ years) within a modern business intelligence tool (Looker preferred)
 * Experience applying software engineering principles (testing, version control, code reviews, CI/CD, etc.) in your working process, to scale analytical development
 * Proven track record of working with data teams in a fast-paced, startup environment
 * Proven track record of successfully working cross-functionally with both technical and non-technical stakeholders
 * Solutions-driven and thrives when given ambiguous, open-ended problems
 * Proven success driving projects through implementation to completion, including stakeholder education and onboarding
 * Obsessed with data protections and privacy (i.e. PII, GDPR, FedRAMP, FIPS, etc.)
 * Hands-on experience using AI tools in your development workflow (e.g., Claude Code, Cursor, AI-assisted dbt and SQL development)

## Description

* Architect, build and maintain efficient and reliable data products (dbt models, pipelines, Looker explores, visualizations, etc.) that enable data driven decision making.
 * Build and maintain ELT pipelines from source systems to data warehouses.
 * Influence strategy and drive execution of our analytical roadmap delivering self-service business intelligence at scale.
 * Provide leadership and mentorship to other engineers fostering collaboration, knowledge sharing and a high bar for quality.
 * Improve end users trust and confidence by driving best practices with regards to data discoverability, observability, lineage and stewardship.
 * Contribute towards a robust data security strategy protecting sensitive information and content.
 * Solve critical business problems through the application of programming, optimization, automation, and analytical skills., Our team thrives at the intersection of human expertise and AI capability. As an AI-forward company, adaptation and continuous learning are part of our daily work. We're looking for teammates who are excited to evolve alongside technology - people who experiment boldly, share their discoveries openly, and help define best practices for AI-augmented work. These professionals thoughtfully integrate AI into their work to deliver exceptional results while maintaining the human judgment and creativity that drives real innovation. During our interview process, you'll have opportunities to showcase how you harness AI to learn, iterate, and amplify your impact., * Architect domain-level AI reinvention: identify the highest-leverage AI opportunities in how we build and scale our data products, secure the resources to test them, and install repeatable mechanisms that lock in proven gains across several teams
 * Build scalable AI-powered systems, such as intelligent pipeline monitoring, automated data quality checks, and AI-assisted development, that change how analytical work gets done across multiple teams
 * Establish governance frameworks and best practices for responsible AI usage at scale within the analytics function

We encourage all candidates to share examples of how they've used AI tools in their work-whether it's AI-assisted SQL generation, LLM-powered data documentation, automated anomaly detection, or other applications. We view AI fluency as a complement to craft, not a replacement for it.