Senior Manager, Data Engineering
NinjaHoldings · Chicago, IL
About this role
## Senior Manager, Data Engineering Founded in 2017, NinjaHoldings works to give everyday Americans better access to financial services than traditional institutions typically provide. Through our CreditNinja and NinjaCard brands, we offer digital banking and lending products designed for consumers often overlooked, paired with incentives that support long-term financial improvement. Our Edge brand extends this expertise to other companies, providing underwriting, fraud detection, and analytics services. Headquartered in Chicago with a distributed global workforce, we’re a lean, growing organization committed to advancing consumer finance in the US. --- ### Job Summary This position will lead the team responsible for the data platforms and pipelines that power reporting, analytics, operational decision making, and future AI capabilities across the company. This is a technical leadership role focused on setting direction, developing the team, and ensuring our data platform continues to evolve with the needs of the business. You should have enough technical depth to step in when needed, participate in architecture discussions, review designs, and help solve difficult problems. Our current stack includes **Snowflake, dbt, Fivetran, Meltano, PostgreSQL, and AWS**. We’re modernizing our warehouse architecture around a **Medallion model** and building a stronger foundation for analytics and AI. We’re looking for someone who views Data Engineering as a **platform capability for the entire company**—not just a team that maintains pipelines and supports reporting. The right person will think beyond today’s reporting requirements, build reliable systems today, and make architectural decisions that give us more options tomorrow. --- ### Key Responsibilities - Lead the Data Engineering team and set the technical direction for our data platform - Own the architecture, reliability, performance, and evolution of **Snowflake, PostgreSQL**, and the pipelines moving data across systems - Lead our transition to a **Medallion architecture** and establish standards for ingestion, transformation, modeling, testing, documentation, and consumption - Own and evolve our modern data stack, including **Snowflake, dbt, Fivetran, Meltano, PostgreSQL, AWS**, and related technologies - Partner with application engineering teams on transactional database design, schema changes, performance, scalability, and reliability - Work with Engineering, Analytics, Product, Finance, Risk, Marketing, and other business teams to turn data needs into reusable, well-designed solutions (not one-off reporting) - Establish strong engineering practices around data quality, automated testing, observability, lineage, security, documentation, and incident response - Improve self-service access to data so teams can safely understand and use data without relying on Data Engineering for every request - Monitor and optimize the platform for performance, scalability, and cost - Build a long-term roadmap balancing current business needs with future platform capabilities, including AI use cases --- ### Leadership Responsibilities - Lead, mentor, and develop a strong team of Data Engineers - Set clear technical standards and expectations while giving engineers ownership - Participate in architecture and design decisions; challenge assumptions; step in technically when needed - Help prioritize work based on business impact, technical risk, reliability, and long-term value - Build a culture
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