About
Payment infrastructure is being rebuilt. As it scales, data becomes load-bearing — transaction health, financial reconciliation, merchant reporting, operational monitoring all need to be as reliable as the payment flows they track.
This is a Series B fintech building payment infrastructure at scale. The data platform is moving from MVP pipelines to scalable production architecture. This hire joins at that inflection point, working closely with the Data Engineering Lead — currently the only person on the data team.
The team is fully remote with a high-ownership culture. You own systems end-to-end, not just pipelines.
What you'll do
- Design, build, and operate scalable event-driven data pipelines with near real-time processing
- Maintain and evolve the data platform from MVP to production architecture, ensuring quality, observability, and reliability
- Develop backend services that expose data to internal platforms and APIs — enabling financial reconciliation, merchant reporting, and operational dashboards
- Own deployment and monitoring of data systems end-to-end
- Collaborate on architecture decisions as the platform scales
- Work across product, engineering, and infrastructure teams to serve downstream data needs
What you'll need
- 5+ years of data engineering or data infrastructure experience with production systems
- Strong Python and SQL; solid experience with large-scale data processing
- Hands-on experience with modern data stack tools: Airflow, dbt, ClickHouse, Snowflake, or similar
- Experience with event-driven and real-time data processing architectures
- Ability to own systems end-to-end — not just pipelines, but monitoring, reliability, and correctness
- Comfortable using AI as part of how you build
Optional Bonus
- Background in payments, fintech, or high-volume transactional data
- Experience with reconciliation systems or financial data infrastructure
Shortlisted candidates will be contacted within 48 hours.
