Note: The job is a remote job and is open to candidates in USA. Weight Watchers is seeking a Senior Data Engineer to scale and strengthen its Python- and Snowflake-based data ecosystem. The role builds resilient data pipelines and analytics capabilities, supports automated self-service workflows, and leads projects and engineering practices that improve platform reliability and trustworthiness.

Responsibilities

• Data Enablement: Support the analytics layer by developing core Looker views and building out our agentic AI infrastructure to derive automated self-service capabilities and reduce reporting bottlenecks
• Pipeline Architecture: Design, build, and scale ELT pipelines that are resilient, efficient, and modular
• Cross-Functional Collaboration: Partner with Finance, Product, and Analytics to ensure our data models solve the right problems
• Data Modeling: Build and maintain analytics schemas (including Star Schemas) that abstract complex logic into user-friendly datasets
• End-to-End Ownership: Lead projects from inception to production, taking accountability for data integrity and the trustworthiness of the platform
• Operational Excellence: Monitor production health using monitoring tools (e.g. Datadog, Monte Carlo) ensuring our data ecosystem remains robust and reliable
• Technical Leadership: Act as a technical lead, conduct code reviews, define engineering culture, and champion best practices

Skills

• 5+ years in data engineering, with at least 2+ years focused on distributed, large-scale cloud data warehouses
• Proven experience with Snowflake performance optimization and cost-governance
• Deep proficiency in Python, with a focus on writing modular, reusable, and testable code (unit/integration tests) for complex data processing
• Expert-level SQL and a sophisticated understanding of data warehousing methodologies to build performant, scalable analytics layers
• Practical experience with modern CI/CD frameworks (e.g., GitHub Actions, Argo CD) to drive engineering velocity and platform stability
• Expertise in architecting and scaling orchestration-as-code workflows (e.g., Prefect or Airflow) to manage complex dependencies and ensure pipeline resilience
• Deep proficiency in deploying monitoring and alerting frameworks (e.g., Datadog) to maximize system uptime while mitigating alert fatigue
• Experience managing business-critical production pipelines with a focus on uptime, data quality, and defining SLAs
• BS/MS in Computer Science, Information Systems, or a related technical field
• Familiarity with Snowflake Cortex/MCP is a plus

Benefits

• Eligible for a comprehensive benefits package
• Eligible for an annual bonus program
• Hybrid work environment

Company Overview

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