Lead Data Engineer - Snowflake

About this role

Position Title: Lead Data Engineer (Snowflake Optimization)

Location: 6 Months with possibility of extension

Duration: Portland, OR (Hybrid 3 days)

Role Summary

The Senior Snowflake Optimization Engineer will lead the assessment, re‑architecture, and optimization of Snowflake data platform.

This role will act as the technical lead and primary onsite interface for Snowflake optimization initiatives, working closely with stakeholders, data engineering teams, and Matillion pipelines.

Key Responsibilities

Snowflake Cost & Performance Optimization

• Assess current Snowflake warehouse usage, sizing, auto‑scaling, and auto‑suspend configurations.
• Identify cost drivers across Matillion jobs, ad‑hoc analytics, and background workloads.
• Optimize warehouse strategies (multi‑cluster usage, workload isolation, resource monitors).
• Analyze query history and execution plans to reduce compute inefficiencies.

Architecture & Re‑engineering

• Review existing Snowflake schemas, tables, tasks, and pipelines for architectural improvements.
• Recommend and implement Snowflake‑native optimizations (dynamic tables, tasks, result caching where appropriate).
• Evaluate opportunities for hybrid compute (external tables, Iceberg, Spark/EMR) where cost‑effective.
• Advise on data lifecycle, retention, and archival strategies to reduce storage footprint.

Matillion & Pipeline Optimization

• Review Matillion ELT jobs for Snowflake best practices (push‑down transforms, avoiding row‑by‑row logic).
• Improve pipeline execution efficiency and runtime SLAs.
• Define reusable optimization patterns and templates.

Governance & Cost Control

• Help establish cost governance, monitoring, and guardrails.
• Support chargeback / show‑back models if required.
• Provide recommendations to ensure savings are sustainable post‑engagement.

Stakeholder & Delivery Leadership

• Act as the onsite technical lead, coordinating with architects, developers, and busi...