Senior Data Engineer, Zocdoc

• Passionate about the inner workings of data platforms and infrastructure
• Excited to tackle both technical and strategic challenges to build reliable, scalable systems
• Motivated to create high-leverage tools that power analytics and data science
• Energized by the opportunity to build tools and processes that directly improve patient and provider experiences through better data
• Autonomous, proactive, and eager to solve complex problems with practical, scalable solutions
• 5+ years of experience in data engineering or platform/infrastructure roles, with a focus on scaling tools and systems
• Expertise in Python or Scala, and strong proficiency in SQL for data modeling and optimization
• Deep experience with data warehouse technologies like Snowflake, including clustering, performance tuning, query profiling, and access management
• Experience with data lake and lakehouse architectures such as Databricks, Delta Lake, Iceberg, or Apache Hudi, and query engines like Athena or Presto
• Proven ability to design and implement scalable ETL pipelines using technologies like dbt for transformation and Databricks for large-scale processing
• Familiarity with managing infrastructure-as-code, job orchestration (Dagster, Airflow), and CI/CD workflows
• A proactive mindset and strong problem-solving skills, especially when troubleshooting complex infrastructure issues
• Excellent collaboration and communication skills to support cross-functional teams and data consumers

Desirable

• We are looking for a Senior Data Engineer (SDE) to join our Data Engineering team
• In this role, you will design, build, and optimize scalable data systems that empower decision-making and innovation at Zocdoc
• You’ll collaborate with cross-functional teams to manage data pipelines, strengthen governance, and improve the tools and processes that help data producers and consumers work together effectively
• This role leads our specialized Data Infrastructure group, which is responsible for building, maintaining, and optimizing the platforms that power data workflows across the company
• You’ll focus on the underlying infrastructure that supports analytics, experimentation, and machine learning—ensuring it runs efficiently, securely, and cost-effectively to improve the healthcare experience for patients and providers
• Designing and maintaining scalable data pipelines for ingestion, transformation, and delivery across multiple data sources
• Collaborating with Analytics Engineers and Product teams to curate datasets and establish data contracts that improve transparency and reliability
• Developing and managing modern data architectures, such as lakehouses and medallion layers, using tools like Databricks, Delta Lake, or Iceberg
• Optimizing Snowflake usage and performance, ensuring data quality and cost efficiency
• Supporting and scaling orchestration platforms (like Dagster), metadata systems (like Unity Catalog or Collibra), and monitoring tools (like Datadog)
• Collaborating with data engineering, analytics engineering, and security teams to deliver stable and efficient infrastructure for diverse workflows
• Building tools, alerting systems, and documentation that ensure reliable operation and developer self-service across our data stack