Big Data Engineer – AML

Tap Growth ai
SG

Job Description

Role Overview

We are seeking a highly skilledBig Data Engineer – AMLto design, build, and optimize scalable data solutions that support Anti-Money Laundering (AML) and financial crime detection initiatives. This role is critical in enabling data-driven insights for transaction monitoring, risk assessment, and regulatory compliance within a banking environment.

You will work closely with data analysts, data scientists, and compliance teams to deliver high-quality, reliable, and secure data pipelines using modern lakehouse architectures.

Key Responsibilities

  • Design, develop, and maintainscalable data pipelinesfor AML and financial data processing
  • Build and optimize data solutions usinglakehouse architectures(e.g., Delta Lake, Databricks, Apache Iceberg)
  • Ingest, transform, and processlarge volumes of structured and unstructured banking data
  • Support AML use cases such as:
  • Transaction monitoring
  • Risk scoring
  • Regulatory reporting
  • Collaborate with cross-functional teams to deliverdata-driven AML insights
  • Ensuredata quality, integrity, and governanceacross all pipelines
  • Optimize data workflows forperformance, scalability, and cost-efficiency
  • Integrate data from multiple sources including:
  • Core banking systems
  • Payment platforms
  • External data providers
  • Implementdata security and compliance controlsaligned with regulatory standards
  • Troubleshoot data issues and provide ongoing support for production systems

Qualifications & RequirementsCore Requirements

  • Proven experience as aBig Data Engineer, preferably within banking or financial services
  • Strong understanding ofAML processes, financial crime data, and compliance requirements
  • Hands-on experience withlakehouse platforms(must-have)
  • Experience with big data technologies such as:
  • Apache Spark
  • Hadoop
  • Kafka or similar
  • Proficiency in at least one programming language:
  • Python
  • Scala
  • Java
  • Experience building and maintainingETL/ELT pipelines
  • Strong knowledge of:
  • Data modeling
  • Data warehousing
  • Distributed systems

Preferred Qualifications

  • Experience withcloud platforms(AWS, Azure, or GCP)
  • Familiarity withreal-time or near real-time data processing
  • Experience working withregulated data environments
  • Exposure todata governance and security frameworks

Skills & Requirements

Technical Skills

Big Data Engineerlakehouse architecturesDelta LakeDatabricksApache IcebergApache SparkHadoopKafkaPythonScalaJavaETL/ELT pipelinesData modelingData warehousingDistributed systemsAMLfinancial crime detectiontransaction monitoringrisk assessmentregulatory compliancebankingfinancial services

Level

mid

Posted

4/7/2026

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