Lead the development of a financial-grade real-time data platform from 0 to 1 (covering data collection, storage, and computation layers), designing an architecture that supports daily processing of petabyte-scale transactional data.
Establish a cloud-native (AWS) data warehouse system integrated with Spark / Flink for unified stream and batch processing, enabling millisecond-level metric computation for payment data.
Interface with the company's full-stack business (e.g., acquiring and issuing) and design data masking workflows and audit solutions that comply with PCI DSS.
Build and maintain data dashboards to support business teams in data-driven decision-making.
Integrate with payment systems to ensure seamless data flow and consolidation.
Responsible for data collection, processing, modeling, and structuring to improve data quality and usability.
Support cross-departmental data needs and promote data standardization and automation.
Work closely with teams such as risk control, compliance, and product to provide data support.
Requirements :
Over 5 years of experience in data engineering or data warehousing, with the capability to independently build data platforms.
Familiar with mainstream big data technology stacks, and proficient in performance tuning for Hadoop / Spark / Flink (e.g., shuffle optimization, checkpoint mechanism).
Skilled in data modeling (Dimensional / Star Schema), ETL processes, and data governance.
Preferred background in payments, finance, or internet industries; familiarity with payment data structures is a plus.
Strong communication, collaboration, and business understanding skills, with the ability to work effectively with product, risk, and compliance teams.
Preferred Qualifications :
Experience in data-related roles within fintech or payment companies
Hands-on experience building data platforms or dashboards from scratch.
Familiarity with compliance-related data processing policies and workflows.