5+ years of hands-on engineering experience in data platforms or backend systems at scale.
Strong experience with production data pipelines using modern processing frameworks.
Deep understanding of data quality, schema management, and governance practices.
Experience with cloud-based data infrastructure and key architectures.
Proven ability in designing systems meeting security and compliance requirements.
Proficiency in programming languages like Python, Java, or Go.
Ability to design internal customer-supporting platforms with thorough documentation.
Responsibilities
Design and build scalable data infrastructure for high-volume data processing.
Drive the architecture for a secure partner data sharing platform.
Build core identity graph components for unifying multi-source data.
Develop systems to enhance data quality and governance across pipelines.
Collaborate with cross-functional teams to define secure data platform capabilities.
Create tooling and frameworks for data consumption and sharing at scale.
Design infrastructure balancing real-time and batch data requirements.
Benefits
Competitive compensation and equity packages
Leading configured work computers of your choice
Flexible paid time off
Fully covered, high-quality healthcare including dependent coverage
Access to One Medical and option to enroll in an FSA
20 weeks of paid parental leave for primary caregivers
Access to industry-leading technology fostering innovation and productivity.
Full Job Description
What You'll Do
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.
What we look for
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.
Nice to have
Experience building partner-facing or externally shared data platforms with strong access control, auditing, and contract management.
Experience with identity resolution, entity matching, graph-based data systems, customer 360 platforms, or knowledge graphs.
Experience in regulated or compliance-driven environments such as fintech, banking, lending, payments, SOC, PCI, or similar domains.
Experience with streaming platforms and real-time data systems such as Kafka, Flink, Spark Streaming, or similar technologies.
Experience with modern data stack technologies such as Snowflake, Databricks, dbt, Airflow, Dagster, Iceberg, Delta Lake, or similar tools.
Familiarity with privacy-preserving data sharing, clean rooms, data contracts, consent management, or fine-grained authorization models.
Experience improving data platform reliability through observability, automated validation, backfills, incident response, and service-level objectives.
Challenging Problems You'll Drive
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.
Perks & Benefits
Competitive compensation and equity packages
Leading configured work computers of your choice
Flexible paid time off
Fully covered, high-quality healthcare, including fully covered dependent coverage
Additional health coverage includes access to One Medical and the option to enroll in an FSA
20 weeks of paid parental leave for the primary caregiver and 8 weeks for all new parents
Access to industry-leading technology across all of our business units, stemming from our philosophy that we should invest in resources for our team that foster innovation, optimization, and productivity
