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're looking for people who share our passion and are driven to tackle challenges, find solutions and make the financial space better for the communities we serve.
Our team is passionate about challenging the status quo of the credit industry by providing people accessible tools to take control of their credit. Executing on our mission requires deep collaboration across our teams to ensure our products reach the people who can benefit from them the most, particularly the 100 million+ Americans who have no or low credit.
About the Role:
As our Staff Data Engineer, you will be responsible for organizing plans that drive outcomes and making a direct impact on our mission. We want you to provide technical leadership to your teammates through coaching and mentorship, and collaborate cross-functionally to implement impactful improvements to our product.
As part of the Self Financial Data Engineering Team, your role will be to ensure that data remains a strategic asset for Self Financial by delivering timely, high-quality, and purpose-built data to our team members. Our team supports Self Financial's internal Analytics, Machine Learning, and Business Intelligence organizations.
What you will do:
- Operates as part of a cross functional product development team that includes Architecture, Infrastructure, and Product Management
- Your primary focus will be on leading the data pipeline, modeling, and populating data schemas within Self Financial's Data Environment for use in business intelligence and data analysis activities.
- Your day-to-day activities will include:
- Collaborating closely with Product Management to translate Self Financial's strategic vision into actionable projects.
- Architecture design, project analysis, work break down and planning.
- Creating Physical and Logical Data Models with large, complex data sets
- Managing data pipeline, ETL/ELT processes using SQL and Python
- Maintaining data lifecycle and quality standards
Who you are:
- 8+ years of experience with database development, database integration, and data analytics tools
- 8+ years of experience designing and implementing complex Data Warehouse and Data Lake data models (Kimball)
- Willingness to embrace the responsibilities of team leadership and accountability for team results
- Proficient in managing Data ETL/ELT with large data sets
- Experience with columnar data structures such as Amazon RedShift
- Familiarity with AWS data warehousing tools
- Experience with common software engineering tools such as Git, JIRA, Confluence and similar platforms
- Familiarity with Apache Airflow and Python
- Excellent listening, interpersonal, written, and oral communication skills
Base salary range: $160,000-195,000 annually. Individual pay and level is based on factors unique to each candidate, including skill set, experience, and other job-related reasons.
We have the compensation and benefits you expect. But there's one thing that Self Financial can offer that many companies cannot: we can positively change the world, while making a profit. We are a team of Builders, empowering our customers to build their dreams.
Our perks include:
- Company equity in the form of Stock Options
- Performance-based bonuses
- Generous employer-paid health, vision and dental insurance coverage
- Flexible vacation policy
- Educational assistance
- Free gym membership
- Casual dress code
- Team building events and activities
- Hybrid work arrangements/schedules
- Paid parental leave
Self Financial requires all employees hired to successfully pass a background check.
We are an Equal Opportunity Employer.
At this time, we are only able to consider applicants who are U.S. Citizens or Green Card Holders for employment opportunities. We appreciate your understanding.
Skills Required
- 8+ years of experience with database development, database integration, and data analytics tools
- 8+ years of experience designing and implementing complex data warehouse and data lake models using Kimball methodology
- Experience managing ETL/ELT processes with large datasets
- Experience with columnar data structures such as Amazon Redshift
- Familiarity with AWS data warehousing tools
- Experience with Git, JIRA, Confluence, or similar software engineering tools
- Familiarity with Apache Airflow and Python
- Willingness to provide team leadership and accountability for team results
- Excellent listening, interpersonal, written, and oral communication skills
- Successful completion of a background check
- U.S. citizenship or Green Card holder status
Self Financial Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Self Financial and has not been reviewed or approved by Self Financial.
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Healthcare Strength — Medical, dental, vision, life, and disability coverage are extensive, complemented by wellness and mental health programs.
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Parental & Family Support — Paid parental leave, fertility benefits, family medical leave, and a structured return-to-work program indicate strong caregiver support.
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Leave & Time Off Breadth — Flexible or unlimited PTO, alongside paid holidays and sick time, provides broad time-away options for work-life balance.
Self Financial Insights
What We Do
Everyone deserves the chance to improve their financial future. We believe financial progress should be within reach for everyone. We exist to enable people to build credit, build savings, and reach their goals. Every role here connects directly to that purpose, and you'll see the impact of your work in real outcomes for real people.
Why Work With Us
It's not every day you have the opportunity to work for a company with a strong mission that has meaningful impact on people's lives. If you're searching for a higher purpose and you're passionate about helping to improve people's financial situation, then Self is just the place.
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