Skip to content

Senior Analytics Engineer

ZocDoc LogoZocDoc
Apply View Organization

Salary

$160,000 - $220,000

Location

New York, NY

Posted

Yesterday

As a Senior Analytics Engineer, you’ll help build and scale the trusted analytics layer that powers decision-making across Product, Operations, Finance, and Go-To-Market. You’ll lead a meaningful slice of our Analytics Engineering roadmap and own high-impact datasets end-to-end including: design, implementation, testing, documentation, rollout and ongoing reliability. This is a hands-on, senior IC role with significant technical ownership and cross-functional influence.

You’ll enjoy this role if you are…

  • Passionate about building scalable data products that power decisions across the entire company
  • Uncompromising when it comes to code quality, clarity, and maintainability
  • Driven by building domain expertise, staying close to business problems and partnering with stakeholders to turn ambiguous questions into reliable datasets and metrics

Your day to day is…

  • Evolving Zocdoc’s analytics layer: building curated datasets, dimensional models, and governed metrics used for reporting and decision-making
  • Designing and implementing production-grade transformations using SQL + dbt, with strong performance, testing, and documentation standards
  • Building and maintaining a semantic layer / metrics framework so teams measure the business consistently and reliably
  • Improving data reliability: SLAs, freshness/quality monitoring, alerting, and incident response for critical tables and metrics
  • Partnering with Data Engineering on upstream improvements (event logging, source-of-truth definitions, ingestion patterns, and new data sources)
  • Enabling self-serve analytics by improving tooling, access patterns, and governance
  • Leading projects end-to-end, including writing design docs, driving alignment, and mentoring peers through reviews and pairing

You’ll be successful in this role if you have…

  • 5+ years in Analytics Engineering / Data Engineering, with ownership of production data models used by multiple teams
  • Expertise in SQL and proficiency in Python (or another general-purpose language) for tooling and automation
  • 2+ years of hands-on dbt experience in production
  • Experience with orchestration (Dagster, Airflow, or equivalent) and building reliable, observable pipelines
  • Experience building tools to enable AI-driven analytics
  • Strong fundamentals in dimensional modeling (e.g., Kimball), event data modeling, and metric definition/standardization

‌