Data Infrastructure Engineer, Imprint

• 5+ years of hands-on engineering experience building data platforms, distributed systems, infrastructure, or backend systems at scale
• Strong experience designing and operating production data pipelines using modern data processing frameworks and orchestration tools
• Deep understanding of data modeling, data quality, schema management, lineage, observability, and governance best practices
• Experience working with cloud-based data infrastructure, including object storage, warehouses, lakehouse architectures, streaming systems, and compute platforms
• Proven ability to design systems that handle complex data access, privacy, security, and compliance requirements
• Strong backend engineering fundamentals, with proficiency in one or more programming languages such as Python, Java, Scala, Go, or Kotlin
• Experience building platforms or services that support multiple internal customers, with thoughtful APIs, abstractions, documentation, and operational support
• Strong systems thinking, with the ability to reason about trade-offs across latency, consistency, reliability, scalability, cost, and developer experience
• Excellent analytical and problem-solving abilities, especially when working with ambiguous requirements and cross-functional stakeholders
• Strong communication skills, with the ability to clearly explain technical decisions, data platform trade-offs, and system behavior to both technical and non-technical audiences
• High ownership mindset with a strong sense of urgency, accountability, and craftsmanship
• Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or equivalent practical experience

Desirable

• The Data Infrastructure Team at Imprint builds the foundational data systems that power our products, decision-making, risk capabilities, and long-term company strategy
• We are responsible for designing reliable, scalable, and secure data platforms that make high-quality data accessible across the organization and enable teams to move quickly with confidence
• Our work sits at the intersection of distributed systems, data engineering, privacy, security, and product enablement
• We build the infrastructure that allows Imprint to responsibly ingest, model, govern, and share data across internal teams and external partners
• As Imprint grows, the Data Infra team will play a critical role in enabling ambitious company-wide initiatives, including a partner data sharing platform and an identity graph that supports our long-term vision for smarter, more personalized, and more trusted financial products
• Design, build, and operate scalable data infrastructure that supports high-volume ingestion, transformation, storage, and access patterns across the company
• Drive the architecture and implementation of a partner data sharing platform, enabling secure, reliable, and governed data exchange with external partners
• Build core components of Imprint’s identity graph, helping unify customer, account, transaction, partner, and behavioral signals to support long-term product and business strategy
• Develop systems that improve data quality, lineage, observability, reliability, and governance across critical data pipelines and datasets
• Partner with Data, Risk, Product, Engineering, Security, and Compliance teams to define data platform capabilities that are secure, auditable, and easy to use
• Build abstractions, tooling, and frameworks that allow engineers and analysts to safely create, discover, consume, and share data at scale
• Design infrastructure for both batch and real-time data use cases, balancing latency, correctness, cost, and operational complexity
• Solve challenging problems around entity resolution, data freshness, schema evolution, access control, privacy boundaries, and partner-specific data contracts
• Improve the reliability and scalability of data systems through automation, monitoring, alerting, incident response, and capacity planning
• Advocate for strong engineering practices in data infrastructure, including reproducible pipelines, clear ownership, robust testing, and operational excellence
• Partner data sharing at scale: Build a platform that allows Imprint to exchange high-value data with partners while maintaining strict guarantees around security, privacy, correctness, freshness, and auditability
• Identity graph foundations: Design systems that connect fragmented data across users, accounts, cards, merchants, partners, and events to create a trusted foundation for future product intelligence
• Data trust and quality: Create infrastructure that makes data reliable by default, with clear ownership, validation, lineage, and automated detection of anomalies before they impact business-critical decisions
• Access control and governance: Build systems that make sensitive data easy to use safely, enforcing the right permissions, policies, and visibility boundaries without slowing teams down
• Real-time and batch trade-offs: Help define when data needs to be immediate, when it needs to be complete, and how to build infrastructure that can support both without unnecessary complexity
• Platform leverage: Turn repeated data engineering patterns into reusable capabilities that improve velocity across Product, Risk, Finance, Analytics, and Engineering teams