Data Engineer (GenAI)

Location: Singapore; hybrid, with at least 3 days in the office

Company

hirify.global is a global payments technology company facilitating transactions between consumers, merchants, financial institutions, and governments across more than 200 countries and territories.

What you will do

• Design, build, and deploy scalable batch and streaming data pipelines using SQL, Hive, and PySpark across lake and lakehouse environments.
• Create dimensional and semantic models, governed finance data marts, and self-service analytics solutions using Power BI, Fabric semantic models, and SSAS Tabular.
• Operationalize production-grade GenAI capabilities, including RAG, prompt chaining, agent workflows, vectorization, chunking, guardrails, and evaluation frameworks.
• Build reusable prompt libraries, evaluation harnesses, vector store abstractions, SDKs, and APIs for Finance use cases.
• Implement CI/CD, data quality testing, deployment automation, observability, lineage, drift and freshness monitoring, and performance and cost optimization.
• Deliver dashboards and certified datasets while embedding privacy-by-design, PII controls, SOX compliance, audit trails, and technical documentation.

Requirements

• Bachelor’s degree, or 3+ years of relevant work experience; a bachelor’s degree with honors in Data Science or Computer Science is required for the preferred profile.
• At least 1 year of hands-on experience building large-scale data processing platforms and using SQL, Hive, or PySpark with Hadoop technologies and cloud platforms.
• At least 1 year of applied GenAI engineering experience with enterprise RAG, prompt engineering, evaluation, guardrails, LLMs, vectorization, chunking, and orchestration frameworks such as LangChain.
• At least 1 year of experience delivering end-to-end Business Intelligence solutions, with knowledge of ETL strategies and data modeling for reporting.
• Understanding of data warehousing, ER modeling, warehouse architecture, feature engineering, and the Big Data ecosystem.
• Availability to work in the Singapore office at least 3 days per week.

Nice to have

• Working knowledge of Machine Learning, Deep Learning, GenAI, and MLOps.
• Familiarity with data administration, security architecture, user provisioning, auditing, YARN, Splunk, Profiler, or Perfmon.
• Experience with Finance Data Analytics or a finance domain.

Culture & Benefits

• Work on data and AI capabilities supporting Finance, product, compliance, and controllership decision-making.
• Collaborate with data analysts, data scientists, software engineers, and cross-functional partners.
• Contribute to secure, reliable, auditable, and reusable data and AI services.
• Hybrid work arrangement with office attendance expectations confirmed by the Hiring Manager.