Staff Data Quality & Governance Engineer

Stripe; Seattle (WA); On-site; USD 190,000 - 270,000; Full time

Job summary

Stripe is seeking a Staff Data Engineer in Seattle within the Data Quality and Governance org to lead scalable data discovery and metadata platforms. You will mentor engineers and drive end-to-end data initiatives to raise data quality standards across the company.

You will collaborate with product and engineering teams to define canonical datasets, ensure trustworthy data, and leverage AI/LLM and streaming tech to scale data pipelines. This role emphasizes autonomy and collaboration.

Qualifications

• Staff-level role with 10+ years building and operating data systems.
• Strong distributed systems fundamentals for high-availability tooling.
• Proficiency in backend languages (Scala/Java/Go) and SQL.
• Excellent cross-functional collaboration and ability to balance trade-offs.
• Customer-focused, autonomous in ambiguous environments.

Responsibilities

• Lead outcomes for a team of engineers, providing mentorship and guidance.
• Build and operate large-scale data discovery, metadata, or catalog platforms.
• Manage data pipelines SLAs and data warehouses supporting stakeholders.
• Collaborate with PMs and teams to ensure trustworthy datasets.
• Leverage AI/LLM capabilities to analyze and improve data quality.
• Drive key data initiatives end-to-end with high quality and timely delivery.

Skills

Leadership

Distributed systems

SQL expertise

Scala/Java/Go

Cross-functional collaboration

Data quality

Education

Bachelor's degree in Computer Science or related field

Tools

Iceberg

Kafka

Flink

Spark

Airflow

Hive Metastore

Pinot

Trino

AWS

Job description

Stripe is seeking a Staff Data Engineer in Seattle within the Data Quality and Governance org to lead scalable data discovery and metadata platforms. You will mentor engineers and drive end-to-end data initiatives to raise data quality standards across the company.

You will collaborate with product and engineering teams to define canonical datasets, ensure trustworthy data, and leverage AI/LLM and streaming tech to scale data pipelines. This role emphasizes autonomy and collaboration.