Junior/Senior Data Engineer

TALENTSIS PTE. LTD.; Singapore; On-site; SGD 60,000 - 100,000; Full time

Job summary

TALENTSIS PTE. LTD. is seeking a Data Engineer to design, build, and maintain scalable data pipelines and platforms for data collection, storage, processing, and analytics. You will work with data scientists, analysts and business stakeholders to deliver reliable data solutions for BI, ML and digital transformation.

The role emphasizes collaboration across teams, data quality, governance and performance improvements, with exposure to modern big data tech and cloud-leaning practices.

Qualifications

• Bachelor's degree in CS/IT/Data Eng or equivalent.
• 2–5 years of experience building and maintaining data pipelines.
• Hands-on with ETL/ELT tools such as Informatica or Talend.
• Strong SQL and Python skills.
• Familiar with data modelling, metadata management, and data warehousing.
• Exposure to Spark/Hadoop/Hive is advantageous.
• Experience with multiple data sources (SQL, PostgreSQL, SAP, APIs, flat files, unstructured data).
• Experience with Power BI, SharePoint, Kubernetes, Docker/Podman, microservices, or DevSecOps is a plus.
• Strong analytical, problem-solving, and communication skills.

Responsibilities

• Design, build, and maintain ETL/ELT pipelines from multiple sources.
• Create 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 define data requirements.
• Monitor pipelines to ensure reliability, SLAs, and performance.
• Perform data validation, cleansing, and quality assurance.
• Implement governance, security, and compliance across data platforms.
• Troubleshoot data pipeline issues and optimize performance.
• Support deployment, testing, and post-implementation maintenance.

Skills

SQL

Python

Data modelling

Metadata management

Data warehousing concepts

Analytical thinking

Communication skills

Problem solving

Education

Bachelor's 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 motivatedData Engineerto 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)