Senior Analytics Engineer

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. 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. Requirements 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.) #J-18808-Ljbffr