Data Engineer, Product

As a Data Engineer at Notion, your primary responsibility will be to build foundational datasets and infrastructure that enhance data accessibility across the company. This includes defining processes for data transformation, constructing pipelines to support various business functions, and partnering with data scientists to meet their analytical needs.

To excel as a Data Engineer at Notion, candidates should have over four years of experience in data engineering, a strong command of SQL, and proficiency in cloud-based data solutions. Knowledge of data modeling methodologies and hands-on experience with Big Data tools are advantageous.

Yes, experience in a fast-growing or SaaS environment is valued for the Data Engineer position at Notion. This background can help you adapt quickly to our dynamic work culture and effectively contribute to the team's initiatives.

Key skills for success as a Data Engineer at Notion include expertise in SQL, familiarity with cloud platforms (like AWS or Azure), experience in building scalable data pipelines, and strong analytical skills to understand complex data challenges and design relevant solutions.

At Notion, Data Engineers work in a collaborative and vibrant office environment in San Francisco. The company fosters a culture of creativity and diversity, where employees are encouraged to innovate, share ideas, and develop impactful data solutions collectively.

In your response, highlight specific examples of projects where you designed or managed data pipelines and ETL processes. Discuss the tools you utilized, the challenges you faced, and how your work improved data accessibility or quality for stakeholders.

Emphasize your communication skills and collaborative spirit. Share examples of how you've gathered requirements from business partners and translated them into technical solutions, ensuring that all stakeholders are aligned during the process.

Discuss your proficiency with SQL by providing examples of complex queries you have written. Focus on specifics like aggregation functions, window functions, and any techniques you use to optimize query performance.

Select an impactful situation where you faced a data-related issue. Walk through the problem, your analytical approach, the solution you implemented, and the positive impact it had on your team or company.

Be sure to mention any cloud platforms you have hands-on experience with, such as AWS, GCP, or Azure. Explain how you’ve leveraged these platforms to build scalable data solutions or pipelines, and any specific tools integrated within those environments.

Discuss strategies you've employed to empower non-technical users to access and analyze data independently. This might include the creation of dashboards, data catalogs, or training sessions that encourage a self-service mindset.

Highlight the importance of data quality in decision-making processes. Discuss any frameworks or practices you follow to ensure data remains accurate and reliable, such as monitoring SLAs or implementing automated data validation checks.

Illustrate your proactive approach to identify performance bottlenecks through monitoring tools and query optimization techniques. Share an example where you successfully improved performance, enhancing user experience or data processing efficiency.

Outline your familiarity with various data modeling methodologies, such as dimensional modeling, star schemas, or snowflake schemas. Provide examples from projects where you successfully applied these methodologies to solve business data challenges.

Express your alignment with Notion’s mission about democratizing software solutions, as well as your enthusiasm for contributing to a company that values creativity, diversity, and innovative data solutions. Reference specific aspects of the role that excite you.