2 hours ago
San Francisco, CA, USA or New York, NY, USASenior
Base Salary
$170k - $230k/yr
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.
Tech Stack
Categories
BackendData Engineering
About Imprint
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