Lead Data Engineer - Retail Media Network

As a Lead Data Engineer , you’ll design and optimize analytics-focused data architectures in Snowflake , enabling reliable, high-performance datasets for BI and data science teams across retail advertising and customer data ecosystems. Preferred Education and Experience Preferred experience: 6+ years in data engineering with demonstrated ownership of end-to-end warehouse/pipeline architecture and delivery in analytics-heavy environments.

Lead Data Engineer – Retail Media Network (Snowflake)
Job Order: 250473
Employment Type: Contract-to-hire
Location: Remote (United States)
Overview
Help power a fast-growing Retail Media Network by building the data foundation that fuels smarter advertising and customer insights. As a Lead Data Engineer, you’ll design and optimize analytics-focused data architectures in Snowflake, enabling reliable, high-performance datasets for BI and data science teams across retail advertising and customer data ecosystems. You’ll own key technical decisions, drive best practices, and lead the evolution of scalable pipelines and models that support both batch and real-time (or near real-time) use cases.
Required Skills

• 6+ years of data engineering experience, including lead-level ownership of delivery and architecture decisions
• Strong, hands-on expertise with Snowflake (required), including:
  • Snowpipe, Streams, Tasks
• Advanced SQL and data transformation expertise
• Python (preferred, especially for Snowpark)
• Proven experience building analytics-focused data warehouses
• Strong understanding of:
  • Dimensional modeling (Star Schema, Snowflake Schema; facts & dimensions)
  • Data warehousing architecture
  • Data quality and governance practices
  • Entity relationships and schema design
  • OLTP vs. OLAP concepts and analytical data lifecycle
  • Medallion architecture concepts

Nice to Have Skills

• Experience with integration/orchestration tools such as dbt, Airflow, and Fivetran
• Background in Retail or Retail Media Network environments
• Familiarity with:
  • Customer data platforms (CDPs)
  • Advertising / attribution datasets
• Experience supporting analytics and BI use cases at scale
• Exposure to AI/ML data pipelines and building AI-ready datasets

Preferred Education and Experience

• Preferred experience: 6+ years in data engineering with demonstrated ownership of end-to-end warehouse/pipeline architecture and delivery in analytics-heavy environments
• Education: Not specified in the provided job details

Work Authorization
Candidates must be authorized to work in the United States.
Additional Details

• Travel: Not specified in the provided job details
• Certifications: Not specified in the provided job details

How to apply: Not specified in the provided job details.