Senior Data Engineer - 12 month FTC @ SmartestEnergy
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Senior Data Engineer (12-Month FTC) at SmartestEnergy
The purpose of this role is to design and implement robust data architectures that support our data strategy, including the development and maintenance of Data Lakehouse, Data Warehouse, Data marts, and associated Data Solutions. This hands-on role involves direct contribution to projects and BAU activities by building and maintaining data platforms to ensure data consistency, integrity, security, and accessibility across the business.
Core Responsibilities
- Design and implement robust data architectures
- Develop and maintain Data Lakehouse, Warehouse, and marts
- Build complex PySpark pipelines and automated notebooks
- Implement metadata-driven ETL frameworks
- Utilize Azure Data Factory, Microsoft Fabric, Synapse Analytics and strong T-SQL skills
- Manage release processes using CI/CD, Azure Devops, ARM Templates, and PowerShell scripting
- Work within Agile/SCRUM delivery frameworks
- Apply Data Designs, Data Modelling and Medallion architectures
What Sets Us Apart?
SmartestEnergy operates globally with offices in the UK, US, and Australia, and embraces flexible working with up to 30 days remote work per year. We are committed to diversity and inclusion, ensuring that every individual is celebrated for their unique contribution.
Work Arrangement
This is a hybrid role: 2 days in-office and 3 days remote. Occasional travel to other offices may be required.
Application Process
Your application will be reviewed by our recruitment team with an average process of 2-3 weeks involving video interviews on Teams and possibly a face-to-face meeting. We are here to support you, including any reasonable adjustments needed.
Key skills/competency
- Data Architectures
- Data Engineering
- PySpark
- ETL Frameworks
- Azure Data Factory
- Synapse Analytics
- T-SQL
- CI/CD
- Agile/SCRUM
- Data Modelling
How to Get Hired at SmartestEnergy
🎯 Tips for Getting Hired
- Research SmartestEnergy's culture: Study their global outreach and tech stack.
- Customize your resume: Highlight your PySpark and Azure skills.
- Showcase project experience: Include large data set handling examples.
- Prepare for technical interviews: Focus on ETL and data architectures.