Data Engineer (Quantexa_Alteryx_SQL_ELK_DevOps_AWS)

MALTEM ASIA PTE. LTD.; Singapore; On-site; SGD 100,000 - 180,000; Full time

Job summary

Maltem Asia is seeking a Data Engineer for a Banking Client based in Singapore. The role focuses on designing and implementing Quantexa-based solutions for Financial Crime (AML/Fraud) and bridging business needs with data/tech teams.

You will translate risk and compliance requirements into scalable data-driven solutions, collaborating with Compliance, Risk, and Operations to deliver robust data infrastructure and quality outcomes.

Qualifications

• 5-10 years of experience in Financial Services / Banking Tech.
• Hands-on experience in Quantexa implementation or similar platforms (Actimize, SAS AML, Feature space).
• Experience using Alteryx, Linkurious or DataWalk is a plus.
• Strong understanding of Entity Resolution and data matching techniques.
• Knowledge of customer and transaction data models.
• Understanding of network / graph-based analytics concepts.
• Solid SQL skills (joins, aggregations, data validation).
• Good understanding of data engineering concepts (ETL pipelines, data modeling, data quality).
• In-depth understanding of Apache Spark architecture, RDDs, DataFrames, and Spark SQL.
• Strong expertise in designing data infrastructure using Hadoop, Spark, and related tools (HDFS, Hive, Pig, etc).
• Experience with OpenShift, Kubernetes for containerization/orchestration.
• Proficiency in Spark, Python, Scala, or Java for data engineering.
• Knowledge ofDevOps practices, CI/CD pipelines, and infrastructure automation tools (Docker, Jenkins, Ansible, BitBucket).
• Experience with Grafana, Prometheus, Splunk is a plus.
• Experience integrating Elasticsearch for data indexing and search applications.
• Solid understanding of Elasticsearch data modeling, indexing strategies, and query optimization.
• Experience with distributed computing, parallel processing, and large datasets.
• Proficient in performance tuning for Spark and Elasticsearch.
• Strong problem-solving and analytical skills; ability to debug complex issues.
• Familiarity with Git and collaborative development workflows.
• Excellent communication and teamwork skills; cross-functional collaboration.
• Experience with cloud platforms (AWS, Azure, GCP) and data services is a plus.

Responsibilities

• Gather and translate business requirements (AML, Fraud, KYC) into functional and data specifications.
• Define entity resolution, matching and network linking logic aligned to business use cases.
• Perform data analysis and mapping across multiple source systems (customer, account, transaction).
• Design logical data pipelines (ingestion, standardization, matching, network generation, scoring).
• Collaborate with Data Engineers to ensure feasibility and alignment of data transformations.
• Support data quality assessment, cleansing rules, and standardization approaches.
• Validate outputs including entity resolution results, network generation, and risk scoring.
• Assist in UAT, defect triage, and business validation of Quantexa outputs.
• Prepare functional documentation (BRD, FRD, mapping documents, data dictionaries).
• Work closely with Compliance, Risk, and Operations stakeholders.

Skills

Entity Resolution

Data Modeling

ETL Pipelines

SQL

Spark Architecture

Python

Scala/Java

Data Quality

Distributed Computing

Problem Solving

Communication

Tools

Quantexa

OpenShift

Kubernetes

Hadoop

Spark

Hive

Pig

Elasticsearch

Grafana

Prometheus

Splunk

Docker

Jenkins

Ansible

Bitbucket

Git

AWS

Azure

GCP

Job description

Maltem Asia is seeking aData Engineer for a Banking Client based in Singapore.

The Data Engineer will support the design and implementation of Quantexa-based solutions for Financial Crime (AML/Fraud). The role will bridge business requirements and data/technology teams, translating risk and compliance needs into scalable data-driven solutions.

Responsibilities:

• Gather and translate business requirements (AML, Fraud, KYC) into functional and data specifications
• Define entity resolution, matching and network linking logic aligned to business use cases
• Perform data analysis and mapping across multiple source systems (customer, account, transaction)
• Design logical data pipelines (ingestion, standardization, matching, network generation, scoring)
• Collaborate with Data Engineers to ensure feasibility and alignment of data transformations
• Support data quality assessment, cleansing rules, and standardization approaches
• Validate outputs including entity resolution results, network generation, and risk scoring
• Assist in UAT, defect triage, and business validation of Quantexa outputs
• Prepare functional documentation (BRD, FRD, mapping documents, data dictionaries)
• Work closely with Compliance, Risk, and Operations stakeholders

Required Skills & Experience:

• 5 to 10 years of experience in Financial Services /Capital Markets / Banking Technology
• Hands-on experience in Quantexa implementation or similar platforms (Actimize, SAS AML, Feature space)
• Relevant alternative experience using Alteryx, Linkurious or DataWalk is an added advantage
• Strong understanding of Entity Resolution and data matching techniques
• Understanding of customer and transaction data models
• Knowledge of network / graph-based analytics concepts
• Solid SQL skills (joins, aggregations, data validation)
• Good understanding of data engineering concepts (ETL pipelines, data modeling, data quality)
• In-depth understanding of Apache Spark architecture, RDDs, DataFrames, and Spark SQL
• Strong expertise in designing and developing data infrastructure using Hadoop, Spark, and related tools (HDFS, Hive, Pig, etc)
• Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration using Kubernetes
• Proficiency in programming languages commonly used in data engineering, such as Spark, Python, Scala, or Java
• Knowledge of DevOps practices, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)
• Experience with Grafana, Prometheus, Splunk will be an added benefit
• Experience integrating and working with Elasticsearch for data indexing and search applications
• Solid understanding of Elasticsearch data modeling, indexing strategies, and query optimization
• Experience with distributed computing, parallel processing, and working with large datasets
• Proficient in performance tuning and optimization techniques for Spark applications and Elasticsearch queries
• Strong problem-solving and analytical skills with the ability to debug and resolve complex issues
• Familiarity with version control systems (e.g., Git) and collaborative development workflows
• Excellent communication and teamwork skills with the ability to work effectively in cross-functional teams
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services is a plus