Senior / Data Engineer

talentsis pte. ltd.; Singapore; On-site; SGD 90,000 - 120,000; Full time

Job summary

talentsis pte. ltd. is seeking a motivated Data Engineer to design, build, and maintain scalable data pipelines and platforms enabling efficient data collection, storage, processing, and analytics.

You will work with data scientists, analysts and business stakeholders to deliver reliable data solutions for BI and ML initiatives. The role emphasizes governance, security, and performance, with opportunities to work across batch, real-time, and streaming data processing.

Qualifications

• Degree in CS/IT/Data Engineering or related field.
• 2–5 years experience building data pipelines and ETL.
• Hands-on with Informatica, Talend, or similar ETL tools.
• Strong SQL and Python skills.
• Familiar with data modelling, metadata management and warehousing.
• Exposure to big data technologies (Spark/Hadoop/Hive) is advantageous.
• Experience with multiple data sources (SQL, PostgreSQL, SAP, APIs, flat files).
• Exposure to Power BI, SharePoint, Kubernetes, Docker/Podman, Microservices or DevSecOps is a plus.
• Excellent analytical, problem-solving and communication abilities.

Responsibilities

• Design, develop, and maintain ETL/ELT pipelines from multiple sources.
• Build scalable data pipelines for batch, near real-time and real-time processing.
• Develop and maintain data models, warehouses, and integration solutions.
• Collaborate with data scientists and stakeholders to deliver high-quality datasets.
• Monitor pipelines for reliability, availability, and performance against SLAs.
• Perform data validation, cleansing, and quality assurance.
• Implement data governance, security, and compliance across platforms.
• Troubleshoot pipeline issues and optimize system performance.
• Support implementation, testing, deployment, and maintenance.

Skills

SQL

Python

Data modelling

Metadata management

Data warehousing

Analytical skills

Communication

Big data concepts

Education

Degree in Computer Science / Information Technology / Data Engineering

Tools

Informatica

Talend

Power BI

SharePoint

Kubernetes

Docker/Podman

Job description

Role Overview:

We are looking for a motivated Data Engineer to design, build, and maintain scalable data pipelines and data platforms that enable efficient data collection, storage, processing, and analytics. You will work closely with data scientists, analysts, and business stakeholders to develop reliable data solutions that support business intelligence, machine learning, and digital transformation initiatives.

Key Responsibilities:

• Design, develop, and maintain ETL/ELT pipelines for structured and unstructured data from multiple sources.
• Build and optimise scalable data pipelines to support batch, near real-time, and real-time data processing.
• Develop and maintain data models, data warehouses, and data integration solutions.
• Collaborate with data scientists and business stakeholders to understand data requirements and deliver high-quality datasets.
• Monitor data pipelines to ensure reliability, availability, and performance against defined SLAs.
• Perform data validation, cleansing, and quality assurance to maintain data integrity.
• Implement data governance, security, and compliance requirements across data platforms.
• Troubleshoot and resolve data pipeline issues while continuously improving system performance.
• Support solution implementation, testing, deployment, and post-implementation maintenance.

Requirements:

• Degree in Computer Science, Information Technology, Data Engineering, or a related discipline.
• 2-5 years of experience in building and maintaining data pipelines and ETL solutions.
• Hands-on experience with ETL/ELT tools such as Informatica, Talend, or similar platforms.
• Strong knowledge of SQL and Python.
• Familiarity with data modelling, metadata management, and data warehousing concepts.
• Exposure to big data technologies such as Apache Spark, Hadoop, or Hive is advantageous.
• Experience working with multiple data sources including SQL databases, PostgreSQL, SAP, flat files, APIs, and unstructured data is preferred.
• Exposure to Power BI, SharePoint, Kubernetes, Docker/Podman, Microservices, or DevSecOps practices will be an added advantage.
• Strong analytical, problem-solving, and communication skills.

(EA Reg No: 20C0312)