Zocdoc Staff Analytics Engineer at Zocdoc responsible for designing and maintaining scalable analytics layers to power strategic analytics and reporting. Role involves collaboration with multiple teams to ensure data solutions meet business needs.
Responsibilities
Zocdoc is seeking a Staff Analytics Engineer to join a centralized team responsible for defining, creating, and maintaining a scalable and robust analytics layer that powers Zocdoc’s strategic analytics, operations, and reporting capabilities. As a Staff-level member, you'll lead the design and implementation of complex data transformations and production-grade data models, establishing standardized datasets that drive critical decision-making across the organization. Collaborating closely with Product Management, Product Engineering, Data Engineering, and Analytics teams, you'll ensure data solutions are strategically aligned, efficient, and consistently reliable, enabling teams across Zocdoc to rapidly gain meaningful insights from high-quality data.
You’ll enjoy this role if you are...
Excited about designing and building strategic data products that drive impactful outcomes across the entire organization
Passionate about solving complex, high-impact problems using data and analytics at scale
Committed to setting a high bar for technical excellence and continuously improving whatever you're working on
A collaborative leader who enjoys working cross-functionally in a supportive and highly cooperative environment
Enthusiastic about architecting scalable data solutions using cutting-edge technologies to support long-term business strategies
Defining and enabling trusted, strategic datasets and analytics solutions that empower data consumers to quickly and reliably gain insights at scale
Leading efforts to enhance self-serve analytics across the organization through advanced administration, adoption strategies, and training for analytics tools (Looker and Amplitude)
Partnering strategically with analysts, product managers, and product engineers to ensure the analytics infrastructure meets evolving business requirements and is robust and maintainable
Architecting and developing production-grade data transformations and models using SQL, DBT, and Dagster, ensuring optimal performance, maintainability, scalability, and reliability
Collaborating closely with data engineering on strategic infrastructure initiatives to enhance data ingestion, processing pipelines, and integration of new data sources
