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Salary: USD 187,000 - 259,000 / annual
Chime's Data Platform team builds the infrastructure that powers engineering and analytics across the company—handling ingestion, transformation, data quality, governance, and self-serve tooling for both batch and streaming workloads.
In this role, you will own core platform systems at scale, design the frameworks other teams depend on, and set technical standards for how data flows through Chime. You'll have high autonomy, work on real architectural trade-offs, and see production impact from day one. Chime is hiring multiple engineers at the senior level for this position.
Key responsibilities:
- Design, build, and operate self-serve ETL/ELT frameworks supporting batch and streaming workloads, with direct ownership of pipeline reliability, data quality SLAs, and schema evolution
- Drive the technical roadmap for the data platform—evaluate build-vs-buy decisions, define integration patterns, and set standards adopted across the company
- 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 platform operations—monitor, alert, debug, and resolve incidents with the urgency expected of infrastructure powering financial products
- Raise the technical bar through code review, design reviews, and hands-on mentorship of junior and mid-level engineers
- Participate in on-call rotation, including responding to incidents outside regular working hours
Chime is a financial technology company (not a bank) that helps millions unlock their financial potential through user-friendly tools and intuitive platforms. The company operates with an owner's mindset, values bold thinking and diverse perspectives, and holds itself to the highest standards of integrity.
Work arrangement: Four days per week in office, Fridays from home for those near an office location. Fully remote options available for some roles.
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 results
- 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)
- 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
- Experience operating in a regulated environment (fintech, healthtech, or similar) where data governance, access control, and audit trails are non-negotiable
