Data Engineer (Jakarta, Indonesia)

Salary Range: IDR 11.800.000 - 25.000.000 (Gross)

Weshine is hiring for our client (ESGpedia Singapore Pte Ltd), based in Singapore, for a digital remote role. ESGpedia Singapore Pte Ltd is an Asia's leading ESG FinTech, underpinning the Monetary Authority of Singapore (MAS)'s Greenprint ESG Registry, enabling financial institutions and corporates across all sectors towards sustainability and net zero.

Job Summary:

We are looking for a Data Engineer to design, build, and scale our data pipelines and infrastructure.

You will play a critical role in enabling real-time analytics, AI-driven insights, and high-quality climate intelligence across our platform. This role sits at the intersection of data engineering, analytics, and machine learning enablement.

You will work closely with backend engineers, AI Data scientists, and product teams to ensure our platform’s data is accurate, reliable, fast, and scalable.

Job Responsibilities:

As a Data Engineer, you will work closely with our Product and Data team to ensure data pipelines can support our client and analytics needs.

Your core responsibilities:

• Design, build, and maintain scalable data pipelines for ingestion, transformation, and processing of large, complex datasets
• Develop real-time and near-real-time data systems to support customer-facing insights
• Build robust ETL / ELT workflows across multiple data sources
• Ensure high data quality, consistency, and observability across pipelines
• Support AI and machine learning workflows, including feature engineering and data preparation
• Optimize data models for analytics, dashboards, and customer reporting
• Improve pipeline reliability, monitoring, alerting, and performance
• Collaborate with product and data analyst teams to translate climate and sustainability requirements into scalable data solutions
• Contribute to architectural decisions as the platform grows
  
  
  

Requirements:

• B.S. or M.S. in Computer Science or equivalent degree or experience
• >3 years of data engineering experience
• Strong experience with Python and SQL
• Hands-on experience building production-grade data pipelines
• Experience with streaming, event-driven or real-time systems
• Solid understanding of data modeling, warehousing, and analytics design
• Familiarity with Cloud platforms (i.e. AWS) and Databricks is a plus
• Familiarity with modern data stack tools (Databricks is a plus)
• Strong engineering fundamentals: testing, version control, CI/CD
• Experience working with a variety of relational and key-value or NoSQL databases (MySQL, Redis)
• Ability to work in a fast-moving startup environment with ownership mindset