Backed by SoftBank VF, ICONIQ and Menlo.
About the role
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. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 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
- A cloud data warehouse (Snowflake, BigQuery, or Redshift)
More about this role
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...
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