Senior Data Engineer: Lakehouse & AI-Ready Platforms

Charterhouse Partnership; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Charterhouse Partnership is assisting a leading financial institution in Singapore to recruit a Senior Data Engineer to design scalable lakehouse platforms, implement governed data products and AI-ready assets.

You will deliver batch and real-time data pipelines, enforce data quality and observability, and partner with AI/data science teams to power NLP, RAG and agent‑driven analytics for banking risk and fraud use‑cases.

Qualifications

• 10+ years hands‑on data‑engineering delivery experience, banking / financial services background preferred

Responsibilities

• Design metadata‑driven ingestion frameworks for structured and unstructured data, covering batch, CDC, streaming, API and file sources
• Develop reusable Spark / Java / Python components; build Bronze‑Silver‑Gold lakehouse layers and implement data modelling, lineage, SLA‑enabled data products
• Tune distributed workloads, implement data quality controls and production observability
• Apply DevOps, CI/CD and IaC on Docker / Kubernetes; operationalise ML models alongside data scientists
• Architect data foundations supporting RAG, agent‑AI and multi‑modal unstructured‑data workflows
• Build internal engineering tooling and align data implementations with financial regulatory requirements
• Troubleshoot production workloads and drive platform reliability improvements

Skills

PySpark

Java

Python

SQL

Data modelling

Lakehouse architecture

ETL/ELT

CDC

NLP

RAG

Cross-team collaboration

Education

Bachelor / Master’s in Computer Science or quantitative‑related discipline

Tools

Docker

Kubernetes

CI/CD

Observability tooling

Iceberg

Kafka

Flink

NiFi

Cloudera Machine Learning

Job description

Charterhouse Partnership is assisting a leading financial institution in Singapore to recruit a Senior Data Engineer to design scalable lakehouse platforms, implement governed data products and AI-ready assets.

You will deliver batch and real-time data pipelines, enforce data quality and observability, and partner with AI/data science teams to power NLP, RAG and agent‑driven analytics for banking risk and fraud use‑cases.