Data Engineering Manager

Data Engineering ManagerSelf 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.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.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. You'll 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 matterAt Self Financial, we put hard problems in the hands of people who've solved them before. Our data platform underpins everything from real-time risk signals to executive reporting, and it's 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 JobAs 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. You'll 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. You'll partner closely with Analytics, Risk, and Platform/Infrastructure teams to make sure the data platform serves real business decisions, not just dashboards.Who You AreYou've been a practitioner in modern data infrastructure you've designed, built, or operated warehouse/lakehouse systems, not just directed others who didYou can read and critique a dbt model, a pipeline DAG, or a schema design and have an informed opinionYou're comfortable being a contributor in a data platform design conversationYou want to manage people, but you don't want to lose your technical edge doing itYou 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 itWhat You'll Be DoingManaging and growing a team of data engineers, including hiring, mentoring, and performance managementOwning architecture and design decisions for our data warehouse, transformation pipelines (dbt), and orchestration layerActively participating in technical design reviews and code/PR reviewsDriving 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 capabilitiesEstablishing and enforcing data platform governance: model maturity standards, access controls, data quality checksEvaluating and introducing new tooling, frameworks, and infrastructure as the platform scalesWhat You'll Have4+ years in a data engineering management or tech-lead-manager role, directly managing engineers7+ years of hands-on data engineering experience - building and operating pipelines, warehouses, or lakehouse platforms in productionSpecific 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 preferredA track record of making architecture decisions that held up in production, not just process improvementsExcellent written and verbal communication skills, including with non-technical stakeholdersExperience with agile engineering methodologiesBase salary range: $170,000-225,000 annually. Individual pay and level is based on factors unique to each candidate, including skill set, experience, and other job-related reasons.Benefits and Perks: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. 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 OptionsPerformance-based bonusesGenerous employer-paid health, vision and dental insurance coverageFlexible vacation policyEducational assistanceFree gym membershipCasual dress codeTeam building events and activitiesRemote work arrangements/ flexible work schedulePaid parental leaveSelf 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.