Senior Data Engineer

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🔥 29 minutes ago

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WeightWatchers

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1963

🏥 Healthcare

🍽️ Food & Beverage

Healthcare • Food & Beverage • Health

WeightWatchers is a health-focused organization that offers personalized weight-loss programs designed to create a sustainable relationship with food. Their approach emphasizes nutritional education, behavior changes, and comprehensive support through expert coaches and a community of members. With features like a mobile app for tracking meals and providing tailored meal plans, WeightWatchers aims to simplify healthy eating and encourage lasting lifestyle changes for improved wellbeing.

📋 Description

• 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. • Design, build, and scale ELT pipelines that are resilient, efficient, and modular. • Partner with Finance, Product, and Analytics to ensure our data models solve the right problems. • Build and maintain analytics schemas (including Star Schemas) that abstract complex logic into user-friendly datasets. • Lead projects from inception to production, taking accountability for data integrity and the trustworthiness of the platform. • Monitor production health using monitoring tools (e.g. Datadog, Monte Carlo) ensuring our data ecosystem remains robust and reliable. • Act as a technical lead, conduct code reviews, define engineering culture, and champion best practices.

🎯 Requirements

• 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. Familiarity with Snowflake Cortex/MCP is a plus. • 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.

🏖️ Benefits

• comprehensive benefits package • annual bonus program