Data Engineering Leader

We are seeking a seasoned Technical Lead to spearhead our data platform efforts. As a key member of our team, you will be responsible for architecting, implementing, and scaling our end-to-end data platform built on AWS S3, Glue, Lake Formation, and DMS.

• Owning the design and scalability of the data lake architecture for both streaming and batch workloads, leveraging AWS-native services.
  
• Leading the development of ingestion, transformation, and storage pipelines using AWS Glue, DMS, Kinesis/Kafka, and PySpark.
  
• Structuring and evolving data into OTF formats (Apache Iceberg, Delta Lake) to support real-time and time-travel queries for downstream services.
  
• Driving data productization, enabling API-first and self-service access to curated datasets for fraud detection, reconciliation, and reporting use cases.
  
• Defining and tracking SLAs and SLOs for critical data pipelines, ensuring high availability and data accuracy in a regulated fintech environment.
  

• At-least 7 years of experience in data engineering.
  
• Deep hands-on experience with AWS data stack: Glue (Jobs & Crawlers), S3, Athena, Lake Formation, DMS, and Redshift Spectrum.
  
• Expertise in designing data pipelines for real-time, streaming, and batch systems, including schema design, format optimization, and SLAs.
  
• Strong programming skills in Python (PySpark) and advanced SQL for analytical processing and transformation.
  
• Proven experience managing data architectures using open table formats (Iceberg, Delta Lake, Hudi) at scale.
  
• Understanding of stream processing with Kinesis/Kafka and orchestration via Airflow or Step Functions.
  
• Experience implementing data access controls, encryption policies, and compliance workflows in regulated environments.
  
• Ability to integrate GenAI tools into data engineering processes to drive measurable productivity and quality gains — with strong engineering hygiene.
  
• Demonstrated ability to lead teams, drive architectural decisions, and collaborate with cross-functional stakeholders.
  

• Experience working in a PCI DSS or any other central bank regulated environment with audit logging and data retention requirements.
  
• Experience in the payments or banking domain, with use cases around reconciliation, chargeback analysis, or fraud detection.
  
• Familiarity with data contracts, data mesh patterns, and data as a product principles.
  
• Experience using GenAI to automate data documentation, generate data tests, or support reconciliation use cases.
  
• Exposure to performance tuning and cost optimization strategies in AWS Glue, Athena, and S3.
  
• Experience building data platforms for ML/AI teams or integrating with model feature stores.
  

We cultivate a dynamic and innovative culture that fuels growth, creativity, and collaboration. Our fast-paced fintech environment thrives on adaptability, agility, and open communication.

We focus on employee development, supporting continuous learning and growth through training programs, learning on the job and mentorship.

We encourage speaking up, sharing ideas, and taking ownership. Embracing diversity, our team spans across Asia, fostering a rich exchange of perspectives and experiences.

Together, we harness the power of fintech and e-commerce to make a meaningful impact on people's lives.

By submitting your application for this job, you are authorizing us to:

• collect and use your personal data, and to disclose such data to any third party with whom we have service arrangements, in each case for all purposes in connection with your job application, and employment with us; and
  
• retain your personal data for one year for consideration of future job opportunities (where applicable).
  

• Mid-Senior level
  

• Full-time