Senior Data Engineer: Scale Pipelines & AI Enablement (Hybrid)

WW International, Inc. (Weight Watchers); New York (NY); Hybrid; USD 155,000 - 175,000; Full time

Benefits offered by this job

Comprehensive benefits package

Annual bonus program

Hybrid work environment

Job summary

WeightWatchers is seeking a seasoned Senior Data Engineer to drive scale and actionability in our data ecosystem. You will strengthen Python and Snowflake-based infrastructure, building core capabilities for dynamic analytics and automated, self-service data workflows.

The role requires 5+ years in data engineering, Snowflake optimization, and expert Python/SQL skills, with a focus on end-to-end ownership and operational excellence.

Qualifications

• 5+ years in data engineering with distributed, large-scale cloud data warehouses
• Snowflake performance optimization and cost governance experience
• Advanced Python development with modular, testable code and data processing
• Expert SQL and data warehousing methodologies
• CI/CD and workflow orchestration tooling experience
• Strong observability and reliability practices with monitoring
• BS/MS in Computer Science, Information Systems, or related technical field

Responsibilities

• Develop core Looker views and self-service analytics capabilities
• Design, build, and scale ELT pipelines for robust data processing
• Collaborate with Finance, Product, and Analytics to model data for insights
• Model analytics schemas and Star Schemas for user-friendly datasets
• Own projects end-to-end, ensuring data integrity and platform trust
• Monitor production health and reliability with tools like Datadog
• Provide technical leadership, code reviews, and engineering best practices

Skills

Data engineering

Python

SQL

Snowflake

CI/CD

Airflow/Prefect

Datadog

Education

BS/MS in Computer Science or related field

Tools

GitHub Actions

Argo CD

Prefect

Airflow

Job description

WeightWatchers is seeking a seasoned Senior Data Engineer to drive scale and actionability in our data ecosystem. You will strengthen Python and Snowflake-based infrastructure, building core capabilities for dynamic analytics and automated, self-service data workflows.

The role requires 5+ years in data engineering, Snowflake optimization, and expert Python/SQL skills, with a focus on end-to-end ownership and operational excellence.