Chime is a financial technology company, not a bank.
Core banking services should be helpful, easy, and free.
Empowers members to take control of their finances and work towards their goals.
Responsibilities
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.
Requirements
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.
Conditions
In-office work policy: four days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location.
Base salary: $187,000 - $259,000 USD.
Full-time employees may also be eligible for bonus(es), competitive equity, and benefits.