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Data Engineer

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Onsite

Data Engineer

Charterhouse Partnership

Data Engineer

Skills

SQL QueriesDockerPythonData ScienceJavaKafkaData AnalysisMachine LearningAIKubernetesNLP / Natural Language ProcessingPySparkApache AirflowTerraform

2 months ago

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Important information


Contract type:

Permanent

Location:

Singapore

Work mode:

Onsite

Published on:

3 September 2026

What they need


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

Desirable:

  • Airflow, Terraform and cloud‑native data‑platform experience

  • Experience with Iceberg, Kafka, Flink, NiFi or Cloudera Machine Learning

Please contact Xuemin at [email protected] for a discussion.

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

Only successful applicants will be notified.

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