Chime Financial, Inc - Senior Software Engineer, Data Platform

• Design, build, and operate self-serve ETL/ELT frameworks supporting both batch and streaming workloads, with direct ownership of pipeline reliability, data quality SLAs, and schema evolution • Drive the technical roadmap for our data platform - evaluate build-vs-buy decisions, define integration patterns, and set standards that engineering teams across the company adopt • Partner with Product Engineering, Data Science, Analytics, and Marketing as a technical lead to design data contracts, onboard new data domains, and scale ingestion without sacrificing governance • Architect and enforce data lineage, schema registry, and access controls across all domains - ensuring compliance with fintech regulatory requirements (SOX, PII handling) • Own the platform - monitor, alert, debug, and resolve incidents across the data platform with the urgency expected of infrastructure that powers financial products • Raise the technical bar of the team through code review, design reviews, and hands-on mentorship of junior and mid-level engineers • Engineers are required to participate in on-call rotation. Being on call may include responding to incidents outside of regular working hours when necessary. • 5+ years building, shipping, and operating data infrastructure in production - not just writing pipelines, but owning their reliability, performance, and cost at scale • Strong system design skills - you’ve written design docs, made trade-offs, and delivered the result • Solid understanding of key metrics for data pipelines and experience building solutions to provide visibility to partner teams • Deep proficiency in Python or Java/Kotlin, with strong opinions on testing, code quality, and maintainability in data-heavy codebases • Production experience with the modern data stack, specifically: • A cloud data warehouse (Snowflake, BigQuery, or Redshift) • Workflow orchestration (Airflow, Dagster, or Prefect) and IaC (Terraform) • At least one streaming technology (Kafka, Flink, or Kinesis) - you understand when batch isn’t enough • Data modeling and transformation frameworks (dbt) • Built or improved observability for data systems - freshness monitoring, row-level quality checks, schema drift detection, and SLA dashboards that engineering and business teams actually trust • Experience operating in a regulated environment (fintech, healthtech, or similar) where data governance, access control, and audit trails are non-negotiable • #LI-Onsite #LI-DA1 • Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible for bonus(es), competitive equity, and benefits. For commissioned roles, the base salary listed in this job description does not include incentive/variable pay. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience. • $187,000 - $259,000 USD