Staff Analytics Engineer (Snowflake)

TL;DR

Staff Analytics Engineer (Snowflake/SQL): Developing and maintaining data infrastructure to fuel reporting and analysis for the Accounting organization with an accent on data modeling and automation. Focus on architecting performant data models, implementing automated testing procedures, and driving organizational improvements in data governance.

Location: Hybrid (Menlo Park, CA) - Must be in-office at least 3 days per week

Salary: $184,000 – $241,500

Company

Snowflake is a cloud-based data platform powering the agentic enterprise through AI-native data solutions.

What you will do

• Build and maintain data infrastructure using SQL, Python, Snowflake, dbt, and Airflow within an agile model.
• Architect flexible, performant data models to establish single sources of truth for the organization.
• Perform data QA and develop automated testing procedures for Snowflake data models.
• Collaborate with IT and technical stakeholders to source data from key business systems.
• Define data governance strategies, including security models, permissions, and data lineage.
• Create and maintain user-friendly documentation for data models and key metrics.

Requirements

• 8+ years of experience as an analytics, data, or BI engineer.
• Advanced SQL skills for standardizing queries and managing large-scale relational datasets.
• Proficiency in Python for parsing, structuring, and transforming data.
• Experience with MPP databases such as Snowflake, Redshift, or BigQuery.
• Must be based in or be able to work from the Menlo Park, CA office at least 3 days per week.

Nice to have

• Experience with ERP and Financial Planning tools.
• Experience using Streamlit for data transformation.
• Knowledge of CI/CD pipelines.
• Experience leading or working within Scrum or other agile frameworks.
• Background in accounting or directly supporting accounting stakeholders.

Culture & Benefits

• Experimental mindset focused on rapidly testing emerging AI capabilities.
• Low-ego, dynamic environment that values curiosity and innovation.
• Opportunity to help redefine the future of work in an AI-native enterprise.
• Scaling team with a high pace of innovation.