Total 4,605 Others data entry job vacancies

·      Administer and manage Redis clusters for low-latency caching and real-time transaction processing.

·      Manage MongoDB clusters (replication, sharding) for scalable transaction and semi-structured data storage.

·      Working knowledge of Hadoop ecosystem (Hadoop, Hive, Pig, Oozie, Hbase, Flume, sqoop) using both automated tool sets as well as manual processes.

·      Support and maintain Hadoop (HDP)clusters for batch processing, analytics, and regulatory reporting.

·      Perform cluster lifecycle management provisioning, scaling, patching, and decommissioning nodes.

·      Ensure 24x7 availability and resilience of production systems supporting payment flows.

·      Manage and optimize Apache Kafka for high-throughput, real-time payment event streaming.

·      Support Apache NiFi for ingestionpipelines from upstream payment systems and external partners.

·      Work with AWS EMR for scalableprocessing of transaction data and reconciliation workloads.

·      Administer HDFS, ensuring optimal replication,storage utilization, and fault tolerance.

·      Manage OpenSearch / Elasticsearchclusters for transaction search, audit trails, and operational dashboards.

Required Skills & Experience

·      6–8 years of experience in Big Data / DataPlatform Engineering in enterprise environments.

·      Strong hands-on experience with:

·      Hadoop ecosystem (HDFS, YARN, MapReduce, HDP)

·      Apache Kafka (high-throughput environments)

·      Redis and MongoDB clusters

·      OpenSearch / Elasticsearch

·      Apache NiFi

·      AWS EMR + good knowledge of AWS Cloud.

·      Strong expertise in Linux system administration and scripting (Shell/Python)

·      Experience with Kerberos, data security, and access governance

·      Proven experience in handling high-volume, low-latency systems (preferably payments/trading) 

EA License No: 11C4879 / Registration ID : R1218583

Apar Technologies Pte Ltd, Singapore

Responsibilities

• Develop and maintain ETL/ELT pipelines using Python, PySpark, and SQL.
• Build and support batch and real-time data processing solutions.
• Integrate data from multiple sources and ensure data quality and reliability.
• Monitor, troubleshoot, and optimize data pipelines and workflows.
• Collaborate with business, analytics, and technology teams to deliver data-driven solutions.
• Support cloud-based data platforms and data warehousing initiatives.
• Develop automation and monitoring solutions to improve operational efficiency.
• Any other ad-hoc duties as assigned by supervisor.

Requirements

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
• 3+ years of Data Engineering or ETL development experience.
• Strong proficiency in Python, PySpark, and SQL.
• Experience with Hadoop, Spark, Kafka, or similar big data technologies.
• Knowledge of data warehousing and data modeling concepts.
• Experience with cloud platforms such as Azure Data Factory, Azure Synapse, Databricks, or Azure Data Lake.
• Strong problem-solving and stakeholder management skills.

Technical Skills

• Experience with Apache Flink or real-time streaming technologies.
• Exposure to Power BI, Tableau, Qlik, or other BI tools.
• Familiarity with AI/LLM frameworks such as LangChain, LangGraph, or RAG solutions.
• Experience within banking, financial services, or large enterprise environments.
• Tech Stack: Python, PySpark, SQL, Hadoop, Spark, Kafka, Azure, Databricks, Power BI/Tableau.

Interested applicants, please email your resume to Andre Chua Jing Ming

Email: andrechua@recruitexpress.com.sg

CEI Reg No: R1989053

EA Licence No: 99C4599

Recruit Express Pte Ltd

Responsibilities

• Develop and maintain ETL/ELT pipelines using Python, PySpark, and SQL.
• Build and support batch and real-time data processing solutions.
• Integrate data from multiple sources and ensure data quality and reliability.
• Monitor, troubleshoot, and optimize data pipelines and workflows.
• Collaborate with business, analytics, and technology teams to deliver data-driven solutions.
• Support cloud-based data platforms and data warehousing initiatives.
• Develop automation and monitoring solutions to improve operational efficiency.
• Any other ad-hoc duties as assigned by supervisor.

Requirements

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
• 3+ years of Data Engineering or ETL development experience.
• Strong proficiency in Python, PySpark, and SQL.
• Experience with Hadoop, Spark, Kafka, or similar big data technologies.
• Knowledge of data warehousing and data modeling concepts.
• Experience with cloud platforms such as Azure Data Factory, Azure Synapse, Databricks, or Azure Data Lake.
• Strong problem-solving and stakeholder management skills.

Technical Skills

• Experience with Apache Flink or real-time streaming technologies.
• Exposure to Power BI, Tableau, Qlik, or other BI tools.
• Familiarity with AI/LLM frameworks such as LangChain, LangGraph, or RAG solutions.
• Experience within banking, financial services, or large enterprise environments.
• Tech Stack: Python, PySpark, SQL, Hadoop, Spark, Kafka, Azure, Databricks, Power BI/Tableau.

Interested applicants, please email your resume to Andre Chua Jing Ming

Email: andrechua@recruitexpress.com.sg

CEI Reg No: R1989053

EA Licence No: 99C4599

Recruit Express Pte Ltd

•You will be responsible for end-to-end delivery of enterprise data and analytics solutions leveraging traditional and modern Data architecture. Experience with Financial Crime Analytics, Finance & Credit Risk Analytics, Credit Scoring & Decision systems, Retail & Wholesale Datamarts will of advantage

•The role spans requirements analysis, solution design, testing, implementation, and production support ensuring high-quality, scalable, and compliant data platforms that support advanced analytics and AI initiatives.

Key Responsibilities

•Lead end-to-end solution delivery for data and analytics across the full SDLC.

•Analyze business and regulatory requirements, translate them into scalable solution designs & provide estimations.

•Communicate complex technical and architectural concepts to business and senior stakeholders in a clear, simplified manner.

•Review and approve test strategies, functional test cases, and data validation approaches.

•Manage risks and issues related to scope, data quality, regulatory commitments, and delivery timelines.

•Participate in product and platform evaluations (RFPs, PoCs) for data, analytics, and AI tooling.

•Partner with production support team to conduct root cause analysis, resolution, and preventive controls.

•Lead innovation and modernization initiatives, including data discovery, cataloguing, governance, and AI enablement.

•Drive productivity, efficiency & quality improvements across delivery and operational processes.

•Ability to design data architectures supporting NLP and AI-driven analytics.

FUNCTIONAL SKILLSETS

Analytics Domains

•Financial Crime Analytics Transaction Monitoring, Customer Due Diligence, Sanctions & Payments Screening

•Finance & Credit Risk Analytics Financial reconciliation, Allocation, Performance management, Regulatory and Management reporting, Credit risk exposure, NPL, Counterparty risk, Basel & IFRS9 input variables

Enterprise Data, Analytics & Unstructured Data Enablement

•Proven experience delivering large-scale analytics platforms within financial services spanning structured, semi-structured, and unstructured data

•Strong capability in requirements analysis and functional design for analytics use cases involving Transactional data, Investigator narratives, Case notes and alerts, Policy & Customer communications documents

•Experience defining data quality, governance, lineage, and reconciliation controls for both structured and NLP-derived datasets.

Unstructured Data & NLP-Enabled Analytics

•Ability to define data architectures and data flows that ingest, curate, and govern unstructured and semi-structured data within enterprise data platforms.

•Experience translating business requirements into NLP-enabled analytical use cases, such as Text classification and categorization, Entity & relationship extraction, Risk indicator identification, Summarization of alerts, cases, or documents

Knowledge Graph & Relationship Based Analytics

•Ability to design and govern an enterprise knowledge layer defining relationship taxonomies, entity resolution rules, and linkage logic

•Ability to translate use cases into relationship driven analytical designs, such as Network based risk identification, Hidden association and indirect exposure analysis, Related party and concentric risk detection

Requirements

Data Platforms & Architecture

•Open table formats: Apache Iceberg, Delta Lake, Apache Hudi

•Distributed processing & query engines: Spark, Trino/Presto, Hive

•Cost optimization strategies: tiered storage, lifecycle management, workload governance

Programming & Analytics

•SQL, BTEQ, GCFR

•Python (Pandas, NumPy)

•BI & visualization tools: Power BI, QlikSense

Data Integration & Quality

•Informatica suite: PowerCenter, BDM, IDQ, Enterprise Data Catalogue

•Data ingestion patterns: batch, CDC, streaming

•Data validation, quality controls, and reconciliation frameworks within environments

Governance, Risk & Compliance

•Data modelling, critical data elements, regulatory reporting

•Fine-grained data access controls (row-level, column-level, masking)

•Metadata management, lineage, and impact analysis

•Compliance with BCBS 239, MAS, AML/CFT, and internal data standards

Big Data Platforms

•Cloudera Hadoop distribution: Hive, Impala, Spark, Iceberg, Trino

Data engineer (Azure) – Synapse and Pyspark, Python, Datawarehouse and Azure Data Explorer, Azure Devops

Job Scope

• Design, review and development of Pyspark scripts. Testing, troubleshooting of data pipelines, orchestration.

• Designing and developing reports and dashboards in PowerBI,setting up access control with row level security DAX query experience.

• Establishing connections to source data systems such as on-prem databases, IOT devices, APIs.

• Managing the collected data in appropriate storage/data-base solutions e.g. file systems, SQL servers, Big Data platforms such as Hadoop, HANA, etc. as required by the specific project requirements.

• Design, development of relevant data pipelines using pyspark, copy data activities for batch ingestion.

• Performing data integration e.g. using database table joins, or other mechanisms at an appropriate level as required by the analysis requirements of the project.

• Deployment of pipeline artifacts from one environment to the other using Azure Devops.

Skills & Experience

• Bachelor’s Degree in Computer Science or Engineering with 2 years of experience in Azure Data engineering, Python, Pyspark or Big Data development.

• Sound Knowledge of Azure Synapse analytics for pipelines, orchestration, set up.

• 1-2 experience in Visualization design and development with Power BI. Knowledge on row-level security, access control.

• Sound experience in SQL, Datawarehouse, data marts, data ingestion with Pyspark and Python.

• Expertise in developing and maintaining ETL processing pipelines in cloud-based platforms such as AWS, Azure, etc. (Azure Synapse or data factory preferred)

• Team player with good interpersonal, communication, and problem-solving skills.

• Preferred to have Devops expertise.

Candidates without prior experience are welcome to apply as on the job training would be provided.

Working hours :

8:30am to 6pm (Monday to Friday) onsite, no hybrid option.

Responsibilities

• Develop and maintain ETL/ELT pipelines using Python, PySpark, and SQL.
• Build and support batch and real-time data processing solutions.
• Integrate data from multiple sources and ensure data quality and reliability.
• Monitor, troubleshoot, and optimize data pipelines and workflows.
• Collaborate with business, analytics, and technology teams to deliver data-driven solutions.
• Support cloud-based data platforms and data warehousing initiatives.
• Develop automation and monitoring solutions to improve operational efficiency.
• Any other ad-hoc duties as assigned by supervisor.

Requirements

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
• 3+ years of Data Engineering or ETL development experience.
• Strong proficiency in Python, PySpark, and SQL.
• Experience with Hadoop, Spark, Kafka, or similar big data technologies.
• Knowledge of data warehousing and data modeling concepts.
• Experience with cloud platforms such as Azure Data Factory, Azure Synapse, Databricks, or Azure Data Lake.
• Strong problem-solving and stakeholder management skills.

Technical Skills

• Experience with Apache Flink or real-time streaming technologies.
• Exposure to Power BI, Tableau, Qlik, or other BI tools.
• Familiarity with AI/LLM frameworks such as LangChain, LangGraph, or RAG solutions.
• Experience within banking, financial services, or large enterprise environments.
• Tech Stack: Python, PySpark, SQL, Hadoop, Spark, Kafka, Azure, Databricks, Power BI/Tableau.

Interested applicants, please email your resume to Andre Chua Jing Ming

Email: andrechua@recruitexpress.com.sg

CEI Reg No: R1989053

EA Licence No: 99C4599

Recruit Express Pte Ltd

Responsibilities

• Develop and maintain ETL/ELT pipelines using Python, PySpark, and SQL.
• Build and support batch and real-time data processing solutions.
• Integrate data from multiple sources and ensure data quality and reliability.
• Monitor, troubleshoot, and optimize data pipelines and workflows.
• Collaborate with business, analytics, and technology teams to deliver data-driven solutions.
• Support cloud-based data platforms and data warehousing initiatives.
• Develop automation and monitoring solutions to improve operational efficiency.
• Any other ad-hoc duties as assigned by supervisor.

Requirements

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
• 3+ years of Data Engineering or ETL development experience.
• Strong proficiency in Python, PySpark, and SQL.
• Experience with Hadoop, Spark, Kafka, or similar big data technologies.
• Knowledge of data warehousing and data modeling concepts.
• Experience with cloud platforms such as Azure Data Factory, Azure Synapse, Databricks, or Azure Data Lake.
• Strong problem-solving and stakeholder management skills.

Technical Skills

• Experience with Apache Flink or real-time streaming technologies.
• Exposure to Power BI, Tableau, Qlik, or other BI tools.
• Familiarity with AI/LLM frameworks such as LangChain, LangGraph, or RAG solutions.
• Experience within banking, financial services, or large enterprise environments.
• Tech Stack: Python, PySpark, SQL, Hadoop, Spark, Kafka, Azure, Databricks, Power BI/Tableau.

Interested applicants, please email your resume to Andre Chua Jing Ming

Email: andrechua@recruitexpress.com.sg

CEI Reg No: R1989053

EA Licence No: 99C4599

Recruit Express Pte Ltd

Contributes to the development of new analytics tool, software, and approaches, including the design, development, troubleshooting and debugging.

  *   Ongoing maintenance, update and support of the existing programming and analytic tools

  *   Develop, implement and maintain server and database infrastructure, hardware and software to ensure maximum tool uptime and performance.

  *   Execute end-to-end data processing workflows, ensuring data is accurately ingested, cleaned and structured across corporate systems.

  *   Manage and monitor data flows between current and future infrastructure components to maintain data integrity and consistency.

  *   Analyze processed data to uncover trends, patterns and operational performance metrics using statistical techniques.

  *   Exercises significant independent judgment to determine best method for accomplishing work and achieving objectives

  *   Leads and /or provides expertise to functional project teams and may participate in cross-functional initiatives.

The requirements:

  *   5 years of hands-on experience in data engineering and analytics

  *   Strong skills in statistical tools and programming languages such as Python, R, etc.

  *   Experience with data analysis / visualization tools and software like Power BI, Looker, Databricks etc.

  *   Proficiency in SQL for data extraction and manipulation.

  *   Attention to detail and a commitment to data accuracy.

  *   Proactive approach to identifying issues and providing solutions.

  *   Strong analytical and problem-solving skills. Ability to analyze complex datasets and translate data into actionable insights.

  *   Ability to present complex information in an understandable and compelling manner.

  *   Excellent written and verbal communication skills

  *   Ability to work independently and collaboratively as part of team

Responsibilities

• Develop and maintain ETL/ELT pipelines using Python, PySpark, and SQL.
• Build and support batch and real-time data processing solutions.
• Integrate data from multiple sources and ensure data quality and reliability.
• Monitor, troubleshoot, and optimize data pipelines and workflows.
• Collaborate with business, analytics, and technology teams to deliver data-driven solutions.
• Support cloud-based data platforms and data warehousing initiatives.
• Develop automation and monitoring solutions to improve operational efficiency.
• Any other ad-hoc duties as assigned by supervisor.

Requirements

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
• 3+ years of Data Engineering or ETL development experience.
• Strong proficiency in Python, PySpark, and SQL.
• Experience with Hadoop, Spark, Kafka, or similar big data technologies.
• Knowledge of data warehousing and data modeling concepts.
• Experience with cloud platforms such as Azure Data Factory, Azure Synapse, Databricks, or Azure Data Lake.
• Strong problem-solving and stakeholder management skills.

Technical Skills

• Experience with Apache Flink or real-time streaming technologies.
• Exposure to Power BI, Tableau, Qlik, or other BI tools.
• Familiarity with AI/LLM frameworks such as LangChain, LangGraph, or RAG solutions.
• Experience within banking, financial services, or large enterprise environments.
• Tech Stack: Python, PySpark, SQL, Hadoop, Spark, Kafka, Azure, Databricks, Power BI/Tableau.

Interested applicants, please email your resume to Andre Chua Jing Ming

Email: andrechua@recruitexpress.com.sg

CEI Reg No: R1989053

EA Licence No: 99C4599

Recruit Express Pte Ltd

We are seeking a Senior Data Engineer to work directly with agencies, enabling them to reach their desired development delivery efficiency and system resiliency through optimized Continuous Integration/Continuous Deployment(CI/CD) and Site Reliability Engineering(SRE) practices.

Asa forward-deployed engineer, you’ll partner with agencies to solve complex challenges, gather insights, and drive continuous improvement in our product offerings. This role combines deep technical expertise with a commitment to customer enablement and feedback, ensuring that our Core Engineering Products evolve to address the real-world needs of our customers.

As a Senior Data Engineer, youwill be working on:

·      Translate data requirements from business users into technical specifications.

·      Collaborate with partner agency’s IT teams on technology stack, infrastructure and security alignment.

·      Build out data product as part of a data team:

·      Architect and build ingestion pipelines to collect, clean, merge, and harmonize data from different source systems.

·      Day-to-day monitoring of databases and ETL systems, e.g., database capacity planning and maintenance, monitoring, and performance tuning; diagnose issues and deploy measures to prevent recurrence; ensure maximum database uptime;

·      Construct, test, and update useful and reusable data models based on data needs of end users.

·      Design and build secure mechanisms for end users and systems to access data in data warehouse.

·      Research, propose and develop new technologies and processes to improve agency data infrastructure.

·      Collaborate with data stewards to establish and enforce data governance policies, best practices and procedures.

·      Maintain data catalogue to document data assets, meta data and lineage.

·      Implement data quality checks and validation processes to ensure data accuracy and consistency.

·       Implement and enforce data security best practices, including access control, encryption, and data masking, to safeguard sensitive data.

What we are looking for:

·      A Bachelor’s Degree, preferably in Computer Science, Software Engineering, Information Technology, or related disciplines.

·      Deep understanding of system design, data structure and algorithms, data modelling, data access, and data storage.

·      Demonstrated ability in using cloud technologies such as AWS, Azure, and Google Cloud.

·      Experience with Databricks.

·      Experience in designing, building, and maintaining batch and real-time data pipelines.

·      Experience with orchestration frameworks such as Airflow, Azure Data Factory.

·      Proficiency in working with Python, Shell Scripts, and SQL.

Preferred requirements:

·      Familiarity with building and using CI/CD pipelines.

·      Familiarity with DevOps tools such as Docker, Git, Terraform.

·      Experience with implementing technical processes to enforce data security, data quality, and data governance.

·      Familiarity with government systems and government's policies relating to data governance, data management, data infrastructure, and data security.

·      Experience in Climate and Weather domains will be an advantage.