Staff Data Engineer
$200,000–$260,000 year
On-siteSunnyvale, California, United States
Job Summary
Design and maintain scalable, reliable batch and streaming data pipelines using Airflow, Beam, and Python, implementing robust data quality checks, testing, and monitoring. Build data models that support cost-effective analytics and machine learning, optimizing complex SQL and streaming logic for performance. Partner with data science, engineering, and product teams to translate ambiguous requirements into actionable solutions and visualize insights via Looker dashboards. Own the technical direction of the data platform, including architecture, standards, and roadmap, while mentoring engineers through code reviews and design discussions. Deliver measurable impact by improving pipeline reliability, cost, and performance, and drive the data platform roadmap from proposal through delivery.
Required Qualifications
- 8+ years in an Analytics Engineering or Data Engineering role
- experience setting technical direction and mentoring other engineers
- Strong proficiency with large-scale query tools such as SQL or Apache Spark
- comfort with Python for data manipulation and building orchestration and streaming pipelines
- Experience developing, maintaining, and monitoring large data pipelines with an orchestration tool (Airflow, Dagster, or dbt) for batch and a streaming framework (Apache Beam, Kafka Streams, Flink, or similar)
- Solid grasp of large-scale data fundamentals — partitioning strategies, SQL query performance optimization, cost/performance tradeoffs
- Experience developing data models that support scalable, cost-effective analytics and ML pipelines
- Experience writing data quality checks and unit and integration tests to ensure high-quality data and analytics
- Experience creating analytics solutions with visualization tools such as Looker or Tableau
- Proficiency with version control (Git)
Desired Qualifications
- Experience building pipelines that support ML model training and serving
- Experience with modern data warehouses such as Snowflake, Databricks, or BigQuery
- Experience with containerization tools such as Docker
- Bachelor's or Master's degree in a relevant field, or equivalent practical experience
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