Senior Data Platform Engineer

About Upstart

Upstart is the leading AI lending marketplace partnering with banks and credit unions to expand access to affordable credit. By leveraging Upstart's AI marketplace, Upstart-powered banks and credit unions can have higher approval rates and lower loss rates across races, ages, and genders, while simultaneously delivering the exceptional digital-first lending experience their customers demand. More than 80% of borrowers are approved instantly, with zero documentation to upload.

Upstart is a digital-first company, which means that most Upstarters live and work anywhere in the United States. However, we also have offices in San Mateo, California; Columbus, Ohio; and Austin, Texas.

Most Upstarters join us because they connect with our mission of enabling access to effortless credit based on true risk. If you are energized by the impact you can make at Upstart, we’d love to hear from you!

The Team

The Data Platform Engineering team (Part of Upstart's core platform vertical) provides developer tools, frameworks, and scalable data infrastructure as shared services across Upstart. The team's primary objective is to provide Data Analysts, Software Engineers, and ML scientists access to high-quality data and developer tools to create business metrics for respective product verticals. 

You will join the subdivision of our Data Platform teams focusing on Data Quality, Governance, and Production Experience (Data Infrastructure). 

As a Senior Data Platform Engineer at Upstart, you will get the opportunity to contribute to 3 areas:

1. Expand the existing developer tools to support Upstart's various data validation & quality checks by integrating with open-source, 3rd party, and custom data quality solutions.
2. Build a framework to capture Data Lineage and location of critical fields and integrate with Upstart's data catalog solution that informs various data handling rules.
3. Improve data infrastructure uptime and observability.

We would love to hear from you if you are passionate about building data products!

 
Position Location - This role is available in the following locations: Remote, San Mateo, Columbus, Austin 

Time Zone Requirements - This team operates across all U.S. time zones.

Travel Requirements - This team has periodic on-site collaboration sessions 2-3 times per year. Upstart will cover all travel related expenses.

 

How you’ll make an impact:

• Participate in planning and prioritization by collaborating with stakeholders across the various product verticals and functions (ML, Analytics, Finance, Legal, Privacy, Security) to ensure our architecture aligns with the overall business objectives.
• Collaborate with Data Governance and Security teams to implement robust privacy requests, data protection mechanisms, access controls, and data lineage.
• Participate in code reviews and architecture discussions to exchange actionable feedback with peers. 
• Contribute to engineering best practices and mentor junior team members. 
• Help break down complex projects and requirements into sprints.
• Continuously monitor and improve data platform performance, reliability, and security.
• Stay up-to-date with emerging technologies and industry best practices in data engineering.
• Design and ship code independently

 

What we’re looking for: 

• Minimum requirements:
  • A bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
  • 5+ years of experience in data engineering or related fields, with a strong focus on data quality, governance, and data infrastructure.
  • Proficiency in data engineering tech stack; Databricks / PostgreSQL / Python / Spark / Kafka / SQL / AWS / Airflow/ DBT / containers and orchestration (Docker, Kubernetes) and others.
  • Ability to approach problems with first principles thinking, embrace ambiguity, and enjoy collaborative work on complex solutions.
• Preferred qualifications:
  • Strong foundation in algorithms and data structures and their real-world use cases.
  • Experience and understanding of distributed systems, data architecture design, and big data technologies (e.g., Spark, Kafka, Lakehouse, Databricks).
  • Experience with AWS technologies ( e.g.,  AWS Lambda, Redshift, RDS, S3, etc.).
  • Knowledge of data quality management, data governance, and data security best practices.
  • Good knowledge of DevOps engineering using Continuous Integration/Delivery tools like Kubernetes, Jenkins, Terraform, etc., thinking abo