Data Engineer (6-Month Contract)

Tookitaki Holding PTE LTD; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A tech firm specializing in financial solutions is seeking a Data Engineer for a 6-month contract in Singapore. The role involves supporting high-priority data initiatives, focusing on building and maintaining robust data pipelines. Ideal candidates will have extensive experience in Apache Spark and Cloudera, with responsibilities including designing pipelines, data validation, and cross-functional collaboration. Join a dynamic team dedicated to enhancing AI-driven financial crime prevention efforts.

Qualifications

• 5–8 years as a Data Engineer, with at least 2 years in Spark-heavy environments.
• Prior experience working with Cloudera Data Platform (CDP) in production.

Responsibilities

• Design and optimize batch and streaming pipelines using Apache Spark.
• Build ingestion pipelines using Kafka, Hive, and Spark for large-scale financial datasets.
• Write and optimize SQL queries to validate data accuracy and ingestion success.

Skills

Apache Spark expertise

Cloudera CDP handling

SQL optimization

Kafka

Airflow orchestration

Python scripting

Bash scripting

Linux environments familiarity

Education

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

Tools

Apache Spark

Cloudera CDP (Hive, HDFS, HBase, Impala/Trino)

Kafka

Airflow

Job description

PositionOverview

JobTitle:DataEngineer(6-MonthContract)

Department:Services

Location:Singapore

ReportingTo:Contract

Duration:6months

Tookitaki is seeking a Data Engineer (Contract) with strong expertise in Apache Spark and Cloudera (CDP) to support high-priority data initiatives for our AI-driven financial crime prevention platforms—FinCense and the AFC Ecosystem. This role will contribute to building and maintaining robust data pipelines that ensure accurate, scalable, and production-grade data processing across real-time and batch workflows.

PositionPurpose

This role is designed to support data engineering efforts during a critical delivery phase. The engineer will work closely with platform, product, and services teams to enable high quality data ingestion, transformation, and availability across Tookitaki’s compliance modules. The work done in this role directly contributes to risk scoring, transaction monitoring, and fraud detection systems for global banks and fintech clients.

KeyResponsibilities

1.Spark-BasedDataDevelopment

• DesignandoptimizebatchandstreamingpipelinesusingApacheSpark.
• DebugperformanceandmemoryissuesinSpark-basedETLprocesses.

2.ClouderaDataPlatform(CDP)Handling

• LeverageHDFS,Hive,Impala/Trino,andHBasewithinClouderatosupportdataworkflows.
• CollaboratewithinfrateamstoensureCDPclusterreliabilityandschemaalignment.

3.PipelineDevelopment&Monitoring

• BuildingestionpipelinesusingKafka,Hive,Sparkforlarge-scalefinancialdatasets.
• SupportAirflow-basedorchestrationandensureproductionSLAsaremet.

4.DataValidation&Debugging

• WriteandoptimizeSQLqueriestovalidatedataaccuracyandingestionsuccess.
• Assistintracingpipelineissuesandexecutingbackfillsifnecessary.

5.Cross-FunctionalCollaboration

• Coordinatewithdatascientists,DevOps,andserviceteamstosupportplatformreleases.
• Deliveronstrictprojecttimelinestiedtoactiveclientdeployments.

QualificationsandSkills

Education

• Bachelor’s/Master’sinComputerScience,Engineering,orrelateddiscipline.

Experience

• 5–8yearsasaDataEngineer,withatleast2yearsinSpark-heavyenvironments.
• PriorexperienceworkingwithClouderaDataPlatform(CDP)inproduction.

TechnicalExpertise

• ApacheSpark(Core,SQL,Tuning)
• ClouderaCDP:Hive,HDFS,HBase,Impala/Trino
• Kafka,Airflow,SQL
• PythonandBashscripting
• FamiliaritywithLinux-basedenvironments
• ExposuretoAWSisaplus

SoftSkills

• Strongproblem-solvingmindset
• Abilitytothriveincontractual,delivery-drivensettings
• Clearcommunicationanddocumentationhabits
• Focusonexecution,quality,andspeed

KeyCompetencies

• DataPipelineOwnership
• BigDataArchitecture
• ExecutionAgilityinProjectTimelines
• CollaborativeImplementationMindset
• OperationalReadinessSuccessMetrics
• On-timedeliveryofassignedpipelinecomponents
• StabilityandperformanceofSparkworkflowsinUATandproduction
• Accuracyofdatavalidationandtransformationlogic
• Cross-teamsatisfactionwithdeliverablesinrolloutsprints