Credit Data Engineer

About Us

At StreetShares, we are on a mission to reinvent small business banking for community financial institutions! Our Atlas Digital Business Banking platform enables banks and credit unions to provide fast and efficient digital financing to America’s growing small businesses.

About The Role:

We are seeking an experienced and insightful Credit Data Engineer to raise the bar in how we support our small-business owner customers and financial institutions. This is a critical role in the Credit and Decision Sciences Team with high company visibility, and the potential to have a high impact on the key aspects of the company's credit innovation strategy and credit infrastructure. There are tremendous opportunities for advancement and professional growth.

The engineer will work side by side with analytics, product development, engineering on various initiatives.

The primary responsibilities of this position include:

1) Data infrastructure and Pipeline Management

• Create and maintain optimal data pipeline architecture. Design and implement data warehouses and schemas for the ETL and machine learning pipelines from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
• Develop programs to scrape and store data from various data sources with automated processes leveraging API calls, stored JSON files, other documents, and files from AWS S3 buckets, and SQL databases.
• Work with data and analytics experts to strive for greater functionality in our data systems.

2) Model Deployment and Data Operations

• Manage machine learning operations to deploy, monitor, maintain, and update data and models in production.
• Hands-on experience implementing production-scale machine learning systems in multiple domains.
• Proficiency in deploying machine learning models by API platforms using flask, AWS API tools, or other applications

3) Analytics

• Work on multiple exploratory analytical projects.
• Develop robust analytics and reporting capabilities related to credit products.

4) Culture and Engagement

• In collaboration with leadership, provide recommendations and best practices to foster a culture of mission-driven results and employee engagement.
• We’re a fast-growing, dynamic company - Responsibilities will evolve!

About You:

• Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets.
• Strong analytic skills related to working with structured and unstructured datasets.
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets.
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Knowledge and experience working with various data sources commonly used in lending/credit analysis are desirable.
• Minimum 4-5 years prior experience and expert level skills with SQL and Python are required.
• Ownership of the assignments, ability to multi-task and deliver quality work products while meeting aggressive deadlines.
• Strong willingness to learn, team player mentality, and a self-starter on assigned tasks.
• Strong presentation and communication skills.
• Undergraduate degree in a related discipline.
• Experience in the financial services industry in credit risk analysis is desired

What We Offer:

• An incredible career growth opportunity with a fast-growing FinTech
• A competitive salary with a full benefit package
• A company stock option program
• Gym membership
• Cell phone reimbursement
• Opportunities for growth and development

We welcome and encourage diversity in our workforce. StreetShares is an equal opportunities employer pursuant to applicable law. All qualified applicants will receive consideration for employment based on experience and skills and without regard to any other characteristic protected by law.