Senior Data Engineer (san Jose, Ca / Seattle, Wa)

Zoom

San Jose, California, US
Minimum: $98,900.00; maximum: $228,700.00; bonus/e...
Hybrid
Snowflake, databricks, dbt, airflow
Sql and data modeling expertise
Apache spark / pyspark experience
Build and scale a modern data platform supporting product analytics, lifecycle marketing, ecommerce insights, and machine learning pipelines in a SaaS environment

Job Summary

  • Build and scale a modern data platform supporting product analytics, lifecycle marketing, ecommerce insights, and machine learning pipelines in a SaaS environment.
  • The Online Data team owns the data foundations that support online product experiences, lifecycle marketing, and revenue analytics, working primarily in Snowflake, Databricks, DBT, with Airflow-based orchestration.
  • Zoom offers a Total Direct Compensation philosophy considering base salary, bonus, and equity value, along with a comprehensive benefits program.

Matching Summary

Build and scale a modern data platform supporting product analytics, lifecycle marketing, ecommerce insights, and machine learning pipelines in a SaaS environment.

Salary

Minimum: $98,900.00; Maximum: $228,700.00; Bonus/Equity: Considered in Total Direct Compensation

Skills & Requirements

Must-have

  • Snowflake, Databricks, dbt, Airflow
  • SQL and data modeling expertise
  • Apache Spark / PySpark experience
  • Event-driven, telemetry, product analytics data
  • Cloud platforms (AWS, Azure, GCP)
  • CI/CD for data pipelines
  • Kafka and Kinesis streaming platforms

Nice-to-have

  • Thoughtful design and code reviews
  • Long-term view of data systems
  • Proactive monitoring and operational rigor
  • Collaboration with cross-functional teams

Key Requirements

  • Solid hands-on experience with cloud data stacks
  • Experience with Snowflake, dbt, Apache Airflow
  • Solid SQL and data modeling
  • Working with Apache Spark / PySpark and Databricks
  • Handle event-driven, telemetry, and product analytics data
  • Apply workflow orchestration, monitoring, data quality best practices
  • Build and maintain machine learning model pipelines
  • Operate across cloud platforms (AWS, Azure, GCP)

Work Rights

Not specified

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