Infrastructure Engineer

Responsibilities

• Design, build, and operate scalable data infrastructure for ingestion, transformation, storage, and data access.
• Architect and implement a secure, reliable, and governed partner data sharing platform.
• Build identity graph components connecting customer, account, transaction, partner, and behavioral signals.
• Develop data quality, lineage, observability, reliability, governance, monitoring, alerting, and incident-response capabilities.
• Create abstractions, tooling, and frameworks that enable engineers and analysts to safely discover, consume, and share data at scale.
• Design infrastructure supporting both batch and real-time workloads while balancing latency, correctness, cost, and operational complexity.
• Solve problems involving entity resolution, schema evolution, access control, privacy boundaries, and partner-specific data contracts.
• Collaborate with Data, Risk, Product, Engineering, Security, and Compliance teams to define data platform capabilities.
• Promote 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 with modern data processing frameworks and orchestration tools.
• Deep knowledge of data modeling, data quality, schema management, lineage, observability, and governance.
• Experience with cloud-based data infrastructure, including object storage, warehouses, lakehouse architectures, streaming systems, and compute platforms.
• Experience designing systems with complex data access, privacy, security, and compliance requirements.
• Proficiency in one or more programming languages such as Python, Java, Scala, Go, or Kotlin.
• Experience building platforms or services for multiple internal customers, including APIs, abstractions, documentation, and operational support.
• Strong systems thinking and ability to evaluate latency, consistency, reliability, scalability, cost, and developer-experience trade-offs.
• Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or equivalent practical experience.
• Preferred experience with partner-facing data platforms, identity resolution, entity matching, graph-based data systems, customer 360 platforms, or knowledge graphs.
• Preferred experience in regulated environments such as fintech, banking, lending, payments, SOC, or PCI.
• Preferred experience with Kafka, Flink, Spark Streaming, Snowflake, Databricks, dbt, Airflow, Dagster, Iceberg, or Delta Lake.
• Preferred familiarity with privacy-preserving data sharing, clean rooms, data contracts, consent management, fine-grained authorization, observability, automated validation, backfills, incident response, and service-level objectives.

Benefits

• Competitive compensation and equity packages.
• Choice of configured work computers.
• Flexible paid time off.
• Fully covered healthcare, including dependent coverage, plus access to One Medical and an FSA option.
• 20 weeks of paid parental leave for primary caregivers and 8 weeks for all new parents.
• Access to industry-leading technology and productivity resources across the company.