Data Engineer

EDGE ( is a B2B fintech on a mission to expand credit access for consumers historically unserved and underserved by the reports and scores of traditional credit bureaus. We’re doing this with risk analytics based on complementary alternative data that reveals a more complete financial picture.

Founded in 2021, Edge is part of a larger family of fintech brands that sits underneath our parent company, NinjaHoldings ( NinjaHoldings’ brands also include CreditNinja, a nationwide online consumer lending business established in 2017, and NinjaCard, a neobanking platform focused on consumers in the emerging credit space.

The EDGE business is at an inflection point where we’ve proven our platform’s value with early adopters and we’re ready to go full-throttle into our target markets. Elevating every aspect of our marketing efforts is a critical element in this planned ramp-up.

Join Edge’s dynamic Data Science & Analytics team and drive the backbone of our high-performance data services.

As a Data Engineer, you’ll collaborate closely with data scientists and platform engineers, leveraging your expertise in Python, data intensive workflows, and distributed computing to power cutting-edge fintech solutions. In this role, you’ll shape data pipelines, optimize workflows, and streamline analytics services, all while navigating a fast-paced startup environment. Your contributions will directly influence the evolution of our analytics capabilities, enabling real-time insights and innovation for our customers.

• Work collaboratively with data scientists and engineers on the team to scope, design, and develop high-performance data analysis services
• Coordinate with the platform and product teams, contributing to the deployment and iterative improvement of our analytics services
• Participate in multiple projects simultaneously, adapting to priorities and thriving in a dynamic, fast-paced environment
• Provide technical expertise and recommendations in assessing new software projects and initiatives

• 2+ Years of hands-on experience in a Data Engineering or Software Engineering role
• Proficiency in Python and its data ecosystem (Pandas, NumPy, etc.).
• Hands-on experience with Kubernetes & Docker for containerization and orchestration
• Strong understanding of distributed and parallel computing principles in data engineering.
• Experience with cloud services, especially AWS (e.g., S3, RDS, EKS).
• Experience designing and consuming gRPC and REST
• Experience with relational databases (Postgres or similar) and proficiency in SQL
• Understanding of machine learning workflows and familiarity with ML Ops tools and practices
• Experience with version control (GitHub) and CI/CD pipelines for data applications
• Strong problem-solving skills and ability to debug and optimize complex workflows

• Experience with Kubeflow
• Experience with Clickhouse and other column-oriented databases
• Proficiency in Go or Rust, with application to data processing

• Competitive salary and benefits package
• Fun, fast-paced work environment
• Dynamic start-up culture
• Ability to make an immediate impact in a growth stage company
• Convenient downtown Chicago office located in the heart of the city
• Equal opportunity employer

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