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Snowflake

Value Engineer – FinOps & Growth Analytics

Reposted 7 Days Ago
In-Office
4 Locations
98K-129K Annually
Mid level
In-Office
4 Locations
98K-129K Annually
Mid level
The FinOps Analytics Consultant will analyze datasets using SQL and Python, model consumption behaviors, and create actionable insights to assist Snowflake's customers.
The summary above was generated by AI

Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level.

We are looking for a highly analytical and technically strong FinOps Analytics Consultant with a quantitative or data science background. In this role, you will use advanced SQL and Python to analyze large-scale datasets, model cloud consumption behaviors, and create data-driven insights for Snowflake customers.

Snowflake platform expertise and FinOps skills are not required — we will train you.
What matters most is your ability to work with complex data, derive insights, think in unit economics, and clearly communicate findings to business and technical stakeholders.

KEY RESPONSIBILITIES
  • Analyze large-scale consumption, workload, and performance datasets to uncover insights, trends, and optimization opportunities.

  • Build unit economic models such as:

    • cost per query

    • cost per TB scanned

    • cost per user

    • efficiency benchmarks across workloads

  • Explore and interpret internal metadata pipelines created by Product/Data Science teams to understand compute, storage, and pipeline behaviors.

  • Translate quantitative findings into clear, actionable insights that help customers reduce waste and improve ROI.

  • Develop reusable analytical frameworks for consumption modeling and workload optimization.

  • Partner with account teams, Sales Engineers, and Value Engineers to support customer conversations with data-backed recommendations.

  • Build customer-facing deliverables using Jupyter notebooks, dashboards, and executive-ready PowerPoint narratives.

  • Continuously refine analytical approaches to improve accuracy, benchmarking quality, and scale of FinOps engagements.

REQUIRED SKILLSQuantitative & Technical
  • 3–5+ years of experience in data science, quantitative analysis, analytics engineering, or applied statistics roles.

  • Strong SQL skills — ability to query, aggregate, model, and interpret large datasets.

  • Strong Python skills (pandas, numpy, data modeling, exploratory analysis).

  • Solid understanding of statistics, experimentation, time series, optimization techniques, or benchmarking.

  • Experience working with large-scale datasets from data warehouses, cloud environments, or analytics platforms.

Analytical Thinking & Insights Storytelling
  • Ability to translate complex data into simple unit economics and business insights.

  • Experience preparing clear executive-level narratives, dashboards, or insights reports.

  • Strong critical thinking and structured problem solving.

Communication & Collaboration
  • Experience presenting findings to non-technical stakeholders.

  • Ability to break complex concepts into simple explanations.

  • Strong ownership mentality, curiosity, and willingness to learn specialized Snowflake tooling.

PREFERRED SKILLS

These areas will be taught on the job:

  • Snowflake workload architecture

  • FinOps principles and cloud economics

  • Cloud computing cost models (AWS/GCP/Azure)

  • Query performance tuning concepts

  • Data platform performance engineering

If you don't know these today, you will learn them here.

Ideal Candidate Traits
  • Quant-driven and intellectually rigorous

  • Strong appetite for exploring complex datasets

  • Exceptional SQL + Python hands-on ability

  • Highly structured in thinking and communication

  • Curiosity about cloud platforms and data engineering

  • Thrives in analytical ambiguity

  • Passionate about driving customer impact with data

Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.

How do you want to make your impact?

For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

Top Skills

Jupyter Notebooks
Python
SQL

Snowflake New York, New York, USA Office

114 W. 41st Street, 16th Floor, New York, NY, United States, 10036

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