Original listing text, shown exactly as published by the company.
What you’ll do
- 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.
If you have some or all of the following, please apply
- 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.)
AI at BetterUp
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.
As a Senior Analytics Engineer, you’ll
- Drive functional strategy for AI adoption, identifying transformational opportunities that create competitive advantage in how we build and scale our data products.
- Build scalable AI-powered systems that fundamentally change how analytical work gets done across multiple teams.
- Serve as a trusted advisor to leadership on AI capabilities, limitations, and strategic implications for our data platform.
- Establish governance frameworks and best practices for responsible AI usage at scale within the analytics function.
- Transform core data and analytics processes through strategic AI integration—including intelligent pipeline monitoring, automated data quality checks, and AI-assisted insight generation.
- Quantify AI impact on key data metrics and make data-driven recommendations for continued investment.
During our interview process, you’ll have opportunities to showcase how you harness AI to learn, iterate, and amplify your impact. 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.
