Infrastructure Engineer

About the role

The Data Infrastructure Team at Imprint is seeking a seasoned engineer to join our dynamic and innovative team. This role is responsible for designing, building, and operating scalable data infrastructure that powers our products, decision-making, risk capabilities, and long-term company strategy.

Responsibilities

• 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.

Requirements

• 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.
• A high ownership mindset with a strong sense of urgency, accountability, and craftsmanship.

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or equivalent practical experience.

Skills

• 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.

Benefits

• Competitive compensation and equity packages
• Leading configured work computers of your choice
• Flexible paid time off
• Full coverage, 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

Pay

Competitive compensation and equity packages

Schedule

Full-time