Job Title: Senior Data Engineer, Capital Markets
Company: Oportun (Nasdaq: OPRT)
Job Type: Full-time (not explicitly stated; inferred from the seniority and benefits listed)
Location: Remote
Salary/Pay: Not specified.
Experience: Senior-level, 8+ years in data engineering, with strong experience in data architecture, ETL, and database management.
Skills Required:
- Programming: strong skills in Python or PySpark, plus experience with Java or Scala
- Data pipelines: building complex end-to-end data pipelines and data integration solutions
- Databases: strong SQL and experience with relational and NoSQL database technologies
- Big data: experience with technologies such as Spark, Kafka, Hadoop, or similar platforms
- Orchestration: tools such as Airflow, Databricks, Jenkins, or similar
- Data systems: designing and operating scalable, reliable, and secure data systems
- Cloud: familiarity with AWS, Azure, or GCP and associated data services
- Agile: experience working in Scrum, Lean, or Kanban environments
- Leadership: mentoring junior engineers and contributing to technical leadership within a team
- Communication: strong written and verbal communication across technical and non-technical teams
Advantage: Databricks experience or certification; experience with AWS Redshift, S3, Azure SQL Data Warehouse, or comparable cloud data services; experience implementing data governance, data quality, or observability frameworks; experience leading cross-functional or multi-month engineering initiatives; experience using AI-assisted engineering tools
Date Posted: Oct 21, 2026
Application Deadline: Nov 20th, 2026
Description:
Oportun is hiring a Senior Data Engineer to design, develop, and maintain data platforms for its engineering group. You will contribute to architectural decisions, mentor junior engineers, and lead the technology effort on large, cross-functional, multi-month initiatives. The company encourages using AI tools to improve productivity and problem-solving. Your work will include:
- Designing and implementing scalable, efficient, and reliable data architectures
- Building and maintaining data pipelines, ETL processes, and integration solutions for structured and unstructured data
- Optimizing pipelines, databases, data warehouses, and data lakes for performance, reliability, scalability, and security
- Partnering with stakeholders to translate business needs into effective data models and solutions
- Establishing data quality standards, validation rules, documentation, and governance practices
- Implementing monitoring and observability practices to improve platform reliability
- Providing technical leadership and leading code reviews
- Mentoring junior engineers
- Owning production issues, including troubleshooting and root-cause analysis
- Leading multiple features and projects and keeping stakeholders informed of progress, risks, and dependencies
How to Apply: Apply here.