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Senior Software Engineer (Data Platform)

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Onsite

Senior Software Engineer (Data Platform)

Chime

Senior Software Engineer (Data Platform)

Skills

KotlinPythonData ScienceJavaKafkaSnowflakeData AnalysisdbtApache AirflowComplianceTerraform

14 days ago

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Important information


Contract type:

Permanent

Salary:

$187,000 – $259,000 / year

Location:

San Francisco, CA, USA

Work mode:

Onsite

Published on:

7 October 2026

What they need


  • Chime’s Data Platform team builds the infrastructure every engineering and analytics team depends on - ingestion, transformation, quality, governance, and self-serve tooling across batch and streaming workloads
  • You’ll own core platform systems at scale, design the frameworks other teams build on, and set the technical standards for how data moves through Chime
  • High autonomy, real architectural trade-offs, production impact from day one. We’re hiring multiple engineers into this role at the senior level
  • 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

Benefits

  • Physical: We believe in taking care of your physical health, so as a Chimer you’ll get medical, dental, and vision insurance, as well as benefits to support your physical activity, family planning, and all of your little Chimers
  • Emotional: We know that staying healthy involves a lot more than doctor’s checkups. We partner with Modern Health to help you navigate your mental health, give monthly Take Care of Yourself Days, and want you to take time off when you need it
  • Financial: We want Chimers to save and feel financially supported, so we offer savings plans with competitive matching, as well as access to financial planning and legal assistance so that you can find your financial peace of mind
  • Social: We’ll celebrate your milestones together with travel stipends, swag, and high-fives and make sure you’re connected to fellow Chimers through our Chime Resource Groups (CRGs) and company events- Solid understanding of key metrics for data pipelines and experience building solutions to provide visibility to partner teams
  • 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
  • Production experience with the modern data stack, specifically:
  • A cloud data warehouse (Snowflake, BigQuery, or Redshift)
  • Strong system design skills - you’ve written design docs, made trade-offs, and delivered the result
  • Data modeling and transformation frameworks (dbt)
  • Experience operating in a regulated environment (fintech, healthtech, or similar) where data governance, access control, and audit trails are non-negotiable
  • Workflow orchestration (Airflow, Dagster, or Prefect) and IaC (Terraform)
  • 5+ years building, shipping, and operating data infrastructure in production - not just writing pipelines, but owning their reliability, performance, and cost at scale
  • At least one streaming technology (Kafka, Flink, or Kinesis) - you understand when batch isn’t enough
  • Deep proficiency in Python or Java/Kotlin, with strong opinions on testing, code quality, and maintainability in data-heavy codebases

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