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Data Engineer

Petredec Singapore

Oil and Gas · 201-500 employees

Sep 03
data-engineer Senior (5-10 yrs) Full-time Singapore
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About the role

The Data Engineer will build and maintain data ingestion pipelines and develop reliable data models to support reporting and analytics. They are also responsible for implementing data governance, security frameworks, and enabling AI and BI initiatives.

What they look for

Data Engineering Data Pipelines Data Ingestion Data Modeling Dimensional Modeling Star Schema Data Governance Data Security Master Data Management Data Cataloging Data Lineage Business Intelligence AI Enablement SQL Cloud Platforms

Requirements

The role requires a hands-on builder capable of shaping the platform's underlying structure from the ground up. Candidates must have experience in data extraction, transformation, and maintaining data quality across enterprise-scale systems.

Full description

Purpose

Build a governed, AI-ready data and analytics platform bringing together business domain data and 3rd party data into a central repository.  This is a mostly greenfield build with the ambition to reach full enterprise coverage plus various third-party inputs over roughly 12-18 months. 

The Data Engineer is the teams’ first hands-on builder responsible for extracting data, building the pipelines and monitoring its health, quality and cost day-to-day.  This is a foundational hire that will shape the platform’s underlying structure as it scales from one domain to the entire business.

Key Responsibilities

Data Extraction & Ingestion

  • Build and maintain batch and near-real-time ingestion pipelines from source systems into data lake
  • Identify and implement best practice extraction methodologies per source

Data Transformation & Modeling

  • Build reliable Bronze/Silver/Gold data pipelines landing raw data, cleaning/transforming it and modelling it (dimensional/star schema patterns) for reporting and analysis
  • Partner directly with business domains to define and implement semantic layer for single source of truth with metrics and entities

Governance & Security Support

  • Apply data classification, role-based access controls and row/column-level security to define/implement governance framework
  • Implement and maintain Master Data, cataloguing, lineage, and business glossary upkeep as new sources are onboarded (along with semantic layer)

AI/BI Enablement

  • Ensure clean, well-documented, and consistent modelling to enable BI and MCP-based query access
  • Support early document-intelligence and knowledge-retrieval pilots

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