Analytics Engineer

Role Overview

Build the core data foundation, manage the data warehouse, and make the warehouse AI-readable. Own data modeling standards, lead data governance practices, and build with security and privacy in mind.

What You Will Do

Design and maintain high-quality data models, marts, and pipelines. Manage warehouse architecture, environments, permissions, performance, cost, data lifecycle, and operational hygiene. Make the warehouse AI-readable and own data modeling standards.

Why It Might Be a Fit

You’ll have room to define standards, choose tools, and ship systems that become company-wide defaults. You’ll own the foundation, build for humans and AI, and have high leverage in data science and stakeholder productivity.

Requirements

• 6+ years of experience as an analytics engineer, data engineer, data scientist, or closely related role.
• Deep SQL expertise.
• Strong data modeling experience.
• Pipeline ownership.
• Warehouse management experience.
• Governance mindset.
• AI-native working style.
• Stakeholder fluency.
• Autonomy and execution.
• Operational judgment.

Benefits

• Snowflake administration, optimization, cost management, or warehouse performance tuning.
• Experience with RBAC, PII handling, data classification, retention policies, audit workflows, or privacy/security reviews.
• Experience with Databricks or other modern data infrastructure.
• Experience building semantic layers, metrics layers, metadata systems, or data catalogs.
• Python experience for data tooling, automation, orchestration, or quality checks.
• Previous experience as an early analytics engineer or data engineer at a high-growth startup.