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Data Engineer

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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

See also

Data Engineering jobs by country — openings, pay and top skills →

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