Role Overview
Join a greenfield build to create governed data foundations for enterprise-wide analytics, business intelligence, and future AI use cases. Work closely with senior stakeholders across commercial, operations, finance, and technology.
What You Will Do
Build and maintain data ingestion pipelines, design and develop ETL/ELT pipelines, create scalable data models, and support AI and analytics initiatives.
Why It Might Be a Fit
This role offers the chance to become one of the first hands-on builders of a modern data platform in a global, asset-heavy industry, with opportunities for growth and autonomy.
Requirements
- 5+ years’ experience in data engineering or equivalent hands-on experience building and operating production data pipelines
- Advanced SQL skills with strong experience working with complex operational or transactional datasets
- Hands-on experience with Azure data services, ideally Azure Data Factory, Azure Synapse, Azure Data Lake, or Microsoft Fabric
- Experience building ETL/ELT pipelines from real-world source systems into a cloud data platform or data lakehouse
- Working proficiency in Python, with exposure to Spark or PySpark for larger-scale transformations
- Good understanding of dimensional modelling, star schema design, semantic layers, or medallion architecture
- Familiarity with Git, version control, CI/CD practices, and engineering standards for data pipelines
- Comfortable working in a greenfield environment where processes, standards, and platform design are still being built
- Strong ownership mindset, with the ability to proactively monitor, troubleshoot, and improve data pipelines
- Ability to work directly with business stakeholders and translate commercial or operational requirements into practical data solutions
- Experience in energy, commodities, shipping, logistics, supply chain, trading, or financial services would be advantageous
- Exposure to Microsoft Purview, Power BI, data governance, data catalogues, API-led data access, or AI-enabled analytics would be a plus
To apply for this job please visit linkedin.com.
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