Data Engineer -6 Months

Data Engineer – Big Data & Data Integration

Role Overview

We are looking for an experienced Data Engineer to design, develop and enhance enterprise-scale data pipelines and data integration solutions. The role will work across structured and unstructured data environments, supporting high-volume data processing, analytics and real-time data requirements.

The ideal candidate will have strong hands-on experience with Talend, SQL/PLSQL, Teradata/Oracle, Hadoop, Spark and Kafka, with exposure to modern data transformation tools such as DBT.

Key Responsibilities

Design, develop and enhance scalable data pipelines, ETL processes and data architecture.

Build and maintain data ingestion pipelines using Talend, integrating data from multiple structured and unstructured sources.

Work with business and technology stakeholders to understand requirements and translate them into robust data engineering solutions.

Develop data transformation, cleansing and processing frameworks to improve data quality and availability.

Build and optimize solutions across traditional databases and Big Data platforms.

Develop and support real-time and streaming data pipelines using Kafka or similar technologies.

Support applications and analytics platforms that consume enterprise data to generate actionable business insights.

Automate manual data processes, ETL workflows and job scheduling to improve operational efficiency.

Optimize existing pipelines for performance, scalability, reliability and data quality.

Participate in UAT, system integration testing and production implementation, ensuring solutions meet business and technical requirements.

Troubleshoot data pipeline, integration and production issues and implement sustainable solutions.

Collaborate independently with business users, architects, developers, analytics teams and other stakeholders to deliver key projects and initiatives.

Technical Requirements

Minimum 5 years of experience in Data Engineering, Big Data, Data Integration or Analytics Engineering.

Strong experience with relational database technologies including Teradata and/or Oracle.

Advanced knowledge of SQL and PL/SQL.

Strong hands-on experience with Talend for ETL, data integration and automated job scheduling.

Experience managing and processing both structured and unstructured data.

Experience with modern data transformation methodologies and tools such as DBT.

Strong knowledge of the Hadoop ecosystem, including:Hadoop / HDFSHiveImpalaSparkScalaHBase

Hands-on experience building real-time/streaming data solutions using Kafka or similar technologies.

Strong understanding of ETL/ELT, data transformation, data cleansing and data integration patterns.

Experience developing automated procedures and production-grade data workflows.

Preferred Experience

Previous experience working within Banking, Financial Services or other large enterprise environments.

Exposure to risk management, regulatory or financial data would be advantageous.

Understanding of project delivery methodologies and production support processes.

Experience working with large-scale, business-critical data platforms.

Candidate Profile

Strong analytical and problem-solving capabilities.

Outcome-driven with the ability to solve complex data and integration challenges.

Able to work independently while collaborating effectively across multiple teams.

Strong stakeholder management and communication skills.

Comfortable working in complex, enterprise-scale technology environments.

PERSOL Singapore Pte Ltd • RCB No. 200007268E

50 Raffles Place, #07-01 Singapore Land Tower, Singapore 048623

EA License No. 01C4394 • JACOB TIJO •EA Registration No. R1113321

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