Weight Watchers - Senior Data Engineer
Requirements
• Experience: 5+ years in data engineering, with at least 2+ years focused on distributed, large-scale cloud data warehouses. • Snowflake Expertise: Proven experience with Snowflake performance optimization and cost-governance. Familiarity with Snowflake Cortex/MCP is a plus. • Snowflake Expertise: • Technical Mastery: • Technical Mastery: • Advanced Software Engineering (Python): Deep proficiency in Python, with a focus on writing modular, reusable, and testable code (unit/integration tests) for complex data processing. • Advanced Software Engineering (Python): • Data Modeling & SQL Mastery: Expert-level SQL and a sophisticated understanding of data warehousing methodologies to build performant, scalable analytics layers. • Data Modeling & SQL Mastery: • Infrastructure & Automation: Practical experience with modern CI/CD frameworks (e.g., GitHub Actions, Argo CD) to drive engineering velocity and platform stability. • Infrastructure & Automation: • Workflow Orchestration: Expertise in architecting and scaling orchestration-as-code workflows (e.g., Prefect or Airflow) to manage complex dependencies and ensure pipeline resilience. • Workflow Orchestration: • Observability & Reliability: Deep proficiency in deploying monitoring and alerting frameworks (e.g., Datadog) to maximize system uptime while mitigating alert fatigue. • Observability & Reliability: • Operational Maturity: Experience managing business-critical production pipelines with a focus on uptime, data quality, and defining SLAs. • Operational Maturity: • Education: BS/MS in Computer Science, Information Systems, or a related technical field. • Education: • Base salary may vary depending on, but not limited to: skills, experience, and location. This role is also eligible for a comprehensive benefits package and annual bonus program. • $155,000—$175,000 USD • At WeightWatchers, our mission is to build a worldwide community connected by healthy habits. If that resonates with you, then we would love to talk. WeightWatchers values developing community within our employee population as well. We have a hybrid work environment to allow our employees to find the right work-life balance.
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. • Data Enablement: • Pipeline Architecture: Design, build, and scale ELT pipelines that are resilient, efficient, and modular. • Pipeline Architecture: • Cross-Functional Collaboration: Partner with Finance, Product, and Analytics to ensure our data models solve the right problems. • Cross-Functional Collaboration: • Data Modeling: Build and maintain analytics schemas (including Star Schemas) that abstract complex logic into user-friendly datasets. • Data Modeling: • End-to-End Ownership: Lead projects from inception to production, taking accountability for data integrity and the trustworthiness of the platform. • End-to-End Ownership: • Operational Excellence: Monitor production health using monitoring tools (e.g. Datadog, Monte Carlo) ensuring our data ecosystem remains robust and reliable. • Operational Excellence: • Technical Leadership: Act as a technical lead, conduct code reviews, define engineering culture, and champion best practices. • Technical Leadership:
Benefits
• $155,000—$175,000 USD • At WeightWatchers, our mission is to build a worldwide community connected by healthy habits. If that resonates with you, then we would love to talk. WeightWatchers values developing community within our employee population as well. We have a hybrid work environment to allow our employees to find the right work-life balance.
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