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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. 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. 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 matter At 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 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. 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 are You've been a practitioner in modern data infrastructure you've 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 You're comfortable being a contributor in a data platform design conversation You want to manage people, but you don't 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 you'll 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 you'll 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: $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 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.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.