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Who we are:
Shape a brighter financial future with us.
Together with our members, we’re changing the way people think about and interact with personal finance.
We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
Team:
SoFi is seeking an experienced and motivated Staff Data Engineer to drive high standard technical solutions for the Data Products team within the SIPS (Spend, Invest, Protect, Save) division - supporting all SoFi Financial Services. The mission of the SIPS Data Engineering team is to support Data Engineering and reporting for SoFi’s Financial Services products. As a technical leader you will lead the vision and strategy to build foundational and critical data models which are highly leveraged across SoFi for analytical, reporting, and machine learning use-cases. Our goal is to empower consumers to make data driven decisions and effectively measure their results by providing high quality, high availability data, and democratized data.
Role:
A talented, enthusiastic, detail-oriented, and experienced Data Engineer who knows how to take on big data challenges in an agile way. This includes big data design and analysis, data modeling, and development, deployment, and operations of big data pipelines. Leads development of some of the most critical data pipelines and data sets, and expands self-service data knowledge and capabilities. This role requires you to live at the cross section of data and engineering. You should have a deep understanding of data, analytical techniques, and how to connect insights to the business, and you have practical experience in insisting on the highest standards on operations in ETL and big data pipelines.
What you’ll do:
- Design and develop robust data models and pipelines to support data ingestion, processing, storage, and retrieval. Evaluate and select appropriate technologies, frameworks, and tools to build scalable and reliable data infrastructure.
- Optimize data engineering systems and processes to handle large-scale data sets efficiently. Design solutions that can scale horizontally and vertically.
- Collaborate with cross-functional teams, such as data scientists, software engineers, and business stakeholders, to understand data requirements and deliver solutions that meet business needs. Effectively communicate complex technical concepts to non-technical stakeholders.
- Optimize data engineering systems and processes to handle large-scale data sets efficiently. Design solutions that can scale horizontally and vertically,
- Enforce data governance policies and practices to maintain data integrity, security, and compliance with relevant regulations. Collaborate with data governance and security teams to implement robust data protection mechanisms and access controls.
What you’ll need:
- A bachelor's degree in Computer Science, Data Science, Engineering, or a related field;
- 8+ years of experience in data engineering and analytics technical strategy.
- Proficiency in data engineering tech stack; Snowflake / PostgreSQL / Python / SQL / GitLab / AWS / Airflow/ DBT and others..
- Proficiency in relational database platforms and cloud database platforms such as Snowflake, Redshift, or GCP
- Experience in managing end-to-end data engineering projects. Planning, execution, and resource management.
- Experience leveraging AI tools in data workflows; Cursor / Claude Code / Co Pilot
- Strong in Python and/or another data centric language.
- Thorough knowledge of data modeling, database design, data architecture principles, and data operations.
- Strong analytical and problem-solving abilities, with the capability to simplify complex issues into actionable plans.
- Experience in the Fintech industry is advantageous.
- This role includes a travel requirement of up to 10–15%.
