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Senior Analytics Engineer (AI)

Grace Ferreira

Full-time · Job · Chicago

About the role

We already have the data. Three years of clickstream events, purchase histories, and customer support interactions from our e-commerce platform — all sitting in Snowflake, mostly untouched. What we don't have is the analytical layer that turns this data into features, metrics, and dashboards that actually drive decisions. You'll build the analytics engineering foundation: semantic data models, feature pipelines for ML consumption, business metric definitions, and Tableau dashboards for the leadership team. You'll also own data quality — if a number in a board deck is wrong, it's your pipeline that needs fixing. This is a senior role with significant influence. You'll define how the company measures success. If you've been the person who builds the data layer that everyone else depends on, and you take pride in getting it right, this role will reward that.

Responsibilities

  • Build semantic data models and feature pipelines in Snowflake
  • Define and maintain business metric definitions used across the company
  • Create Tableau dashboards for leadership and cross-functional teams
  • Own data quality monitoring and alerting for critical pipelines
  • Partner with ML engineers to design feature stores for model training

Requirements

  • 5+ years in analytics or data engineering
  • Expert-level SQL and Snowflake experience
  • Strong Python skills with pandas and data transformation libraries
  • Experience with Airflow for pipeline orchestration
  • Track record of building trusted, well-documented data assets

Benefits

  • Fully remote — US time zones
  • Senior compensation with annual bonus
  • Full benefits including 401k match
  • $3,000 professional development budget

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

data science & analytics MLOps & AI Infrastructure

Skills

python sql snowflake spark airflow tableau pandas

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