Data Engineer

Ninja Holdings was founded in 2017 by a team seeking to revolutionize the way everyday Americans interact with financial services. Through our Credit Ninja and Ninja Card brands, we empower people overlooked by traditional financial institutions to take control of their finances via a full suite of digital banking and lending products, providing incentives and rewards along the way as we guide them on a path to financial improvement.

Through our Ninja Edge brand, we help companies better understand their customers by offering a package of bespoke underwriting, fraud detection, and analytics services. With offices in Chicago, Miami, and around the world through the power of remote work, we are a lean and innovative team always seeking like‑minded talent to join us in our fight to disrupt consumer finance.

As a (Sr.) Staff Data Engineer, you will define the technical strategy for enterprise data systems, leveraging Snowflake and dbt to ensure scalability and extensibility aligned with the organization’s long‑term business roadmap. You will provide architectural leadership while remaining a highly effective individual contributor (IC), directly building and optimizing data pipelines, Snowflake environments, and dbt transformations. Your role combines strategic vision with hands‑on execution, requiring you to design robust data solutions and independently implement critical components to support analytics, reporting, and operational needs.

You will lead through analysis, design, collaboration, and mentorship, driving data excellence across the organization.

You may work in the following Data Domains, each comprising multiple systems:

• Analytics & Reporting
  :
  Systems enabling business intelligence, dashboards, and data‑driven insights.
• Data Integration
  :
  Managing data ingestion, transformation, and sharing across platforms.
• Governance & Compliance
  :
  Systems ensuring data quality, security, and regulatory adherence.
• Operational Data
  :
  Supporting real‑time and batch processing for business operations.

• Provide architectural leadership across interdependent data engineering teams, systems, and business units, focusing on Data Platform solutions.
• Design and connect data systems to deliver clean, discoverable, and high‑quality data across analytics, operations, and product teams using scalable data sharing and modular transformation practices.
• Partner with business stakeholders to enhance the data stack, addressing needs such as data governance, compliance, performance optimization, and advanced analytics.
• Elevate your teammates’ expertise in cloud data architecture, transformation workflows, and data modeling best practices.
• Contribute to the design and review of critical data components, including schemas, models, and data pipelines.
• Provide critical thinking, technical innovation, and meticulous attention to detail as a trusted advisor and mentor to your team.
• Support quality assurance, validation, and performance testing to ensure data system reliability, functionality, and efficiency.

• 10+ years of experience in data architecture, data engineering, or related fields, with a focus on designing enterprise data systems, including hands‑on experience building data pipelines or optimizing data platforms
• 5+ years of hands‑on experience with modern cloud‑based data platforms, preferably Snowflake, including expertise in SQL scripting, virtual compute resources, data ingestion pipelines, change data capture mechanisms, task orchestration, and data sharing capabilities
• 3+ years of experience with modern data transformation frameworks, preferably dbt, focused on modular data modeling, incremental processing, automated testing, and comprehensive documentation
• Demonstrated experience contributing in an Agile environment, building cloud‑based data solutions (e.g., AWS, Azure, Google Cloud) with Snowflake as the core platform
• Proven track record of leading data projects from inception to completion and mentoring data engineers or analysts
• Deep understanding of building scalable data architectures, including data lakes, warehouses, and lake houses
• Experience designing and…