Staff Engineer — Data Platform

The stack is modern: StarRocks as our primary analytical layer, Flink for processing, DBT for transformation, Airflow for orchestration and various tooling for surfacing insights.

The hard work of making it super reliable is still in front of us — and that's exactly why this role exists.

Define architecture within the data platform, structure and deliver projects and initiatives end-to-end.

Act as a technical reference point for the Data team, setting quality standards, testing, observability, data modeling, and documentation.

Lead the design and implementation of scalable, low-latency data pipelines that process high-volume payment transactions in real time.

Champion an AI-first engineering culture, establishing standards for AI-assisted development, automated data quality testing, and LLM-powered data workflows.

Design and build data pipelines for large volumes of payment data that are performant, reliable, and correct — not just fast.

Design scalable data models that support business-critical use cases: fraud detection, revenue analytics, payment success rate optimization, regulatory reporting.

Own platform reliability — SLAs, data quality, alerting, and incident response for data services.

Ensure secure data handling practices aligned with PCI-DSS, GDPR, and other compliance frameworks relevant to the payments industry.

Partner with Product, AI, and Finance teams to translate business needs into scalable data solutions.

Contribute to the roadmap of the data platform and proactively identify opportunities to unlock new business value through data.

Mentor senior and mid-level engineers, raising the technical bar across the team through code reviews, design reviews, and knowledge-sharing sessions.

Collaborate with Data Consumers (analysts, data scientists, product managers) to ensure data products are reliable, well-documented, and fit for purpose.