Data Engineer

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DUOTECH

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Job Summary


Job Type
-

Seniority

Years of Experience
Information not provided

Tech Stacks
Python SQL R Analytics AWS ETL

Job Description

About Duotech

Duotech is a Singapore-based technology company specialising in the consulting, design and engineering of customised software solutions and mobile applications. We help organisations drive innovation, improve operational efficiency and strengthen their competitive advantage through tailored, scalable technology solutions.Our team of experienced software experts works closely with clients to understand their unique business challenges and deliver streamlined, high-impact solutions that enhance productivity and support sustainable growth.


Overview of role

The Data Engineer is responsible for building and maintaining scalable data pipelines for both batch and real-time streaming data, managing the data warehouse, and supporting business analytics needs. The role collaborates closely with Data & Analytics and Development teams to integrate data from multiple sources, ensure reliable data infrastructure, and deliver automated reporting and visualization solutions for stakeholders.


Job Responsibilities

  • Maintain and enhance the company’s data warehouse and analytics environment, which consolidates data from multiple internal and external sources.
  • Design, implement, test, deploy, and maintain secure, stable, and scalable data engineering solutions and pipelines supporting analytics initiatives, including batch and real-time streaming data integration.
  • Integrate new data sources into the central data warehouse and enable data delivery to downstream applications and systems.
  • Develop automated reports and data visualizations using data from the warehouse and other integrated sources.
  • Build scalable and reusable code to automate repetitive data engineering and data management tasks.
  • Perform ad-hoc data manipulation and analysis across diverse datasets to support business needs.
  • Implement and monitor best-in-class data security, governance, and reliability practices across the data infrastructure.


Requirements

  • Strong proficiency in relational databases and SQL, with hands-on experience performing ETL processes into relational database systems.
  • Proficiency in Python or R for data manipulation, analysis, and building automated data processing workflows.
  • Solid data wrangling skills, including data cleaning, transformation, restructuring, merging datasets, and format conversion.
  • Proven capability to write clean, well-documented, and maintainable code managed in version control systems such as Git-based repositories.
  • Experience integrating systems via APIs to extract and distribute data across platforms.
  • Familiarity with cloud infrastructure platforms such as Amazon Web Services is preferred.

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