Data Engineer, Product

Notion • San Francisco, CA

10d • $179,000 - $200,000 • Hybrid

About The Position

Notion is hiring a Data Engineer to build reliable data foundations that support product and company growth. The role designs and builds trusted datasets that help product and business teams make decisions and influence the product roadmap. It partners with data scientists and stakeholders to understand data needs and create scalable pipelines, automated workflows, and tools for self-service data exploration.

The position is based at Notion’s San Francisco headquarters. Employees work in the office on Mondays, Tuesdays, and Thursdays (Anchor Days).

Requirements

• At least 5 years of experience as a data engineer building core datasets and supporting business functions.
• Passion for analytics, data modeling, and solving complex problems.
• Strong understanding of scalable cloud data solutions, including AWS, GCP, or Azure, and multiple data stores such as Snowflake, Redshift, Hive, SQL/NoSQL, and columnar formats.
• Knowledge of data methodologies such as dimensional modeling, data marts, and schemas.
• Expert SQL skills, including aggregation, window functions, UDFs, self-joins, and query optimization.
• High proficiency with object-oriented programming in Python, Java, or Scala.
• Expertise using AI and agent-based tools to accelerate data development, including defining guardrails, workflows, and context for safe, production-scale data work.
• Ability to identify high-impact needs with business partners, design technical solutions, and communicate deliverables, timelines, and tradeoffs clearly.

Nice To Haves

• Experience at a fast-scaling or SaaS company; current Notion users are especially welcome.
• Hands-on experience designing and building highly scalable, reliable data pipelines using tools such as Airflow, DBT, Spark, Hive, Parquet/ORC, or Protobuf/Thrift.

Responsibilities

• Define ETL processes and infrastructure to make data readily available across the company.
• Build core datasets that serve as sources of truth for product, marketing, sales, finance, customer experience, data science, operations, IT, and engineering teams.
• Partner with data scientists and stakeholders to understand needs and design, build, and monitor scalable data pipelines.
• Implement automated workflows that reduce operational costs.
• Define SLAs for timely data delivery.
• Democratize data through self-service dashboards, discovery tools, and AI-enabled exploration.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed