You will design, build, and operate event-driven, near real-time data pipelines and the backend systems that serve them. You will maintain data platform reliability, ensure data quality and observability across transactional payment workflows, and build APIs and services to expose data for reconciliation, reporting, and product analytics. You will own deployments, monitoring, and incident response for systems you build and collaborate with product and infrastructure partners to onboard new data use cases.
Responsibilities
- Design and build scalable event-driven data pipelines
- Operate and evolve a real-time data platform from MVP to production
- Model and process transactional and ledger-style data
- Ensure data accuracy, freshness, and observability across workflows
- Build monitoring and alerting to meet financial data reliability requirements
- Own data quality from ingestion through transformation to consumption
- Develop backend services and APIs to expose data to internal systems
- Support downstream use cases including reconciliation and merchant reporting
- Deploy, monitor, and operate production systems end-to-end
- Contribute to documentation, engineering standards, and operational playbooks
Requirements
- 5+ years of experience in data engineering or data infrastructure
- Proven experience building and operating production data pipelines and platforms
- Expertise in SQL and large-scale data processing
- Strong programming skills in Python or similar backend languages
- Experience with event-driven architectures and real-time or near real-time processing
- Experience with modern data stack tools such as Airflow, dbt, ClickHouse, BigQuery, Snowflake, or Athena
- Experience designing systems with data quality, monitoring, and reliability in mind
- Comfortable using AI-assisted development tools with disciplined review and productionization
- Ability to operate independently and own production systems in a remote, asynchronous environment