Staff Data Engineer

About Self Financial

Self Financial is a venture-backed, high-growth FinTech company with a mission to increase economic inclusion and financial resilience by empowering people to build credit and build savings.

We challenge the status quo of the credit industry by giving people accessible tools to take control of their credit, with a focus on the 100 million+ Americans who have no or low credit. We're looking for people who share our passion, tackle challenges, find solutions, and make the financial space better for the communities we serve.

Title

Staff Data Engineer

Team

Data Engineering Team. Ensures data remains a strategic asset for Self by delivering timely, high-quality, purpose-built data to our Analytics, Machine Learning, and Business Intelligence organizations. The team works within a cross-functional product development group that includes Architecture, Infrastructure, and Product Management.

Location: Austin, TX.

Work Arrangement: Austin – Hybrid or Remote.

About the Role

As Staff Data Engineer, you'll drive plans that deliver outcomes and make a direct impact on our mission. You'll provide technical leadership through coaching and mentorship, and work cross-functionally to turn Self's strategic vision into impactful product and data improvements. Your primary focus is leading the data pipeline, modeling, and population of data schemas in Self's data environment for business intelligence and analysis.

What you'll do

• Partner with Product Management to translate strategy into actionable projects
• Lead architecture design, project analysis, work breakdown, and planning
• Create physical and logical data models for large, complex data sets
• Manage data pipelines and ETL/ELT processes using SQL and Python
• Maintain data lifecycle and quality standards

What You Bring

• 8+ years of experience in database development, database integration, and data analytics tools
• 8+ years designing and implementing complex Data Warehouse and Data Lake models (Kimball)
• Proficiency managing ETL/ELT with large data sets
• Willingness to take on team leadership and accountability for team results
• Experience with common engineering tools such as Git, JIRA, and Confluence
• Excellent listening, interpersonal, written, and verbal communication skills

What Separates You

• Experience with columnar data structures such as Amazon Redshift
• Familiarity with AWS data warehousing tools
• Familiarity with Apache Airflow and Python

Base Salary Range

$160,000 – $195,000 annually. Individual pay and level are based on factors unique to each candidate, including skill set, experience, region, and other job-related reasons.

Benefits & Perks

• Generous health, dental, and vision insurance coverage
• Employer-paid benefits including life, disability, and cost-containment resources
• Hybrid work arrangement
• Flexible vacation
• Company performance-based bonuses
• Paid parental leave
• Company equity in the form of stock options
• Education reimbursement program
• Relocation bonus to move to Austin
• Gym membership options through ClassPass or monthly reimbursement
• Lunchdrop stipend
• Paid parking
• ERG and inclusion opportunities
• Casual dress code
• Team building events and activities
• Referral program

Equal Opportunity Employer

Self Financial is an Equal Opportunity Employer. We celebrate diversity and are committed to an inclusive environment. We do not discriminate on the basis of any protected group status under applicable law. If you need an accommodation during the application or interview process, please let us know.

Work Authorization

We can only consider candidates who are U.S. citizens or permanent residents (green card holders). We are unable to offer visa sponsorship of any kind, now or in the future. All new hires must successfully pass a background check.

AI Integrity Policy

Self Financial is an AI-forward company. Our interview process is designed to understand your own career experience, technical acumen, and communication skills. Please do not use AI tools to generate or assist with your answers during interviews unless we explicitly invite you to. If we have reason to believe AI was used in a way that misrepresents your own abilities, we may remove you from the interview process and from consideration for future opportunities at Self.