Data Engineering Manager

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.

Were 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.

We celebrate diversity and are committed to creating an inclusive environment for all employees. To that end we seek to recruit develop and retain the most talented people from a diverse candidate pool.

As a Data Engineering Manager on our Data Platform team you will lead a small high-leverage team responsible for the infrastructure and pipelines that power credit decisioning risk analytics and financial reporting across Self Financial. Youll stay hands-on with the architecture reviewing designs unblocking hard technical problems and setting direction on our data warehouse transformation layer and orchestration while managing and growing a team of data engineers. This is a working technical manager role not a generalist engineering management role: we need someone who has actually built and operated modern data platforms not just managed teams that did.

Teams that make a difference; individuals that matter

At Self Financial we put hard problems in the hands of people whove solved them before. Our data platform underpins everything from real-time risk signals to executive reporting and its undergoing active modernization including a multi-quarter migration toward a lakehouse architecture. We want a leader who can go deep in design reviews not just in headcount planning. This role presents an incredible opportunity for you to have a before and after transformation of an enterprise data warehouse in your career.

About the Job

As Data Engineering Manager you will own the health reliability and roadmap of our core data pipelines and platform services while directly managing a team of data engineers. Youll split your time between hands-on technical leadership architecture reviews pairing with engineers on hard problems evaluating tooling and infrastructure choices and traditional people management: hiring mentoring performance and process. Youll partner closely with Analytics Risk and Platform/Infrastructure teams to make sure the data platform serves real business decisions not just dashboards.

Who you are

• Youve been a practitioner in modern data infrastructure youve designed built or operated warehouse/lakehouse systems not just directed others who did
• You can read and critique a dbt model a pipeline DAG or a schema design and have an informed opinion
• Youre comfortable being a contributor in a data platform design conversation
• You want to manage people but you dont want to lose your technical edge doing it
• You care about data quality governance and reliability as much as throughput.
• You like the idea of helping people build (or rebuild) their financial future through the data that powers it

What youll be doing

• Managing and growing a team of data engineers including hiring mentoring and performance management
• Owning architecture and design decisions for our data warehouse transformation pipelines (dbt) and orchestration layer
• Actively participating in technical design reviews and code/PR reviews
• Driving our modernization roadmap including our migration to Iceberg/Spark and to build a warehouse in medallion-tier architecture.
• Partnering with Analytics Risk and Infrastructure teams to translate business and reporting needs into platform capabilities
• Establishing and enforcing data platform governance: model maturity standards access controls data quality checks
• Evaluating and introducing new tooling frameworks and infrastructure as the platform scales

What youll have

• 4 years in a data engineering management or tech-lead-manager role directly managing engineers
• 7 years of hands-on data engineering experience - building and operating pipelines warehouses or lakehouse platforms in production
• Specific experience with a modern data stack: a cloud data warehouse (e.g. Redshift Snowflake BigQuery) a transformation framework (e.g. dbt) and an orchestration tool (e.g. Airflow Dagster)
• Working knowledge of streaming/event pipelines (e.g. Kafka) and lakehouse table formats (e.g. Iceberg Delta Lake) is strongly preferred
• A track record of making architecture decisions that held up in production not just process improvements
• Excellent written and verbal communication skills including with non-technical stakeholders
• Experience with agile engineering methodologies

Base salary range: $00 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 theres 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. We have a Do the Right Thing ethos in all that we do and we hope you value that approach too.

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
• Remote work arrangements/ flexible work schedule
• 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.