Data Engineer

Charterhouse Partnership; Singapore; On-site; SGD 150,000 - 230,000; Full time

Job summary

Charterhouse Partnership is seeking a Senior Data Engineer for a leading financial institution in Singapore to design and implement scalable lakehouse platforms and governed data products. You will deliver batch and real‑time data pipelines, ensure data quality and observability, and collaborate with AI/data science teams to power NLP, RAG and agent‑driven analytics for banking risk and fraud use‑cases.

The role requires 10+ years of hands‑on data engineering experience, strong

Qualifications

• 10+ years hands-on data-engineering delivery experience, banking / financial services background preferred
• Strong skills in PySpark, Java, Python, advanced SQL; solid knowledge of data modelling, lakehouse architecture, ETL/ELT and CDC
• Practical experience building ingestion pipelines and data products; working familiarity supporting RAG / NLP / agent‑AI workloads
• Hands-on with Docker, Kubernetes, CI/CD and observability tooling
• Able to translate business & risk requirements into data-platform designs; good cross-team communication
• Bachelor / Master’s in Computer Science or quantitative‑related discipline
• Experience with Iceberg, Kafka, Flink, NiFi or Cloudera Machine Learning

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

ETL/ELT

CDC

Docker

Kubernetes

Education

Bachelor/Master in Computer Science or quantitative-related discipline

Tools

Docker

Kubernetes

CI/CD

Observability tooling

Job description

A leading financial institution is seeking a Senior Data Engineer to build scalable lakehouse platforms, governed data products and AI‑ready data assets in close collaboration with architecture, governance, analytics and business stakeholders.

You will deliver batch & 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.

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

Requirements:

• 10+ years hands‑on data‑engineering delivery experience, banking / financial services background preferred
• Strong skills in PySpark, Java, Python, advanced SQL; solid knowledge of data modelling, lakehouse architecture, ETL/ELT and CDC
• Practical experience building ingestion pipelines and data products; working familiarity supporting RAG / NLP / agent‑AI workloads
• Hands‑on with Docker, Kubernetes, CI/CD and observability tooling
• Able to translate business & risk requirements into data‑platform designs; good cross‑team communication
• Bachelor / Master’s in Computer Science or quantitative‑related discipline
• Experience with Iceberg, Kafka, Flink, NiFi or Cloudera Machine Learning

EA License no.: 16S8066 Rep no.: R25157345

Only successful applicants will be notified.