Job Title : Data Solution Architect (AWS, Energy, ML)
Contract Type : 1-Year Contract, Hybrid (London)
Location : London, United Kingdom
Job Description :
We are seeking an experienced Data Solution Architect to join a leading energy company on a key project focused on building cloud-based Machine Learning (ML) models to optimize energy trading (purchase, selling, and generation). This is a hybrid role, based in London , offering the opportunity to work with cutting-edge technologies in a dynamic environment.
In this role, you will collaborate closely with the client to architect and implement solutions that leverage AWS cloud infrastructure and Business Intelligence (BI) tools. The successful candidate will have strong client-facing skills , as this is a pivotal role in a highly visible project.
Key Responsibilities :
- Design and architect cloud-based ML models to optimize energy trading processes.
- Lead the implementation of AWS-based solutions for data analytics and machine learning.
- Collaborate with stakeholders to gather requirements and translate business needs into technical solutions.
- Work closely with data scientists and engineers to ensure seamless integration of ML models with existing systems.
- Provide leadership in the cloud adoption journey and ensure best practices in data architecture .
Must-Have Skills :
- Strong expertise in Amazon Web Services (AWS) , including services like SageMaker, EC2, Redshift, and Lambda.
- Experience with Business Intelligence (BI) and Data Exploration solutions (e.g., Power BI, Tableau, SQL).
- Proven background in the energy sector , specifically in trading optimization for energy purchase, selling, and generation.
- Excellent client-facing and communication skills.
Nice-to-Have Skills :
- Familiarity with machine learning libraries and model deployment in AWS.
- Experience with data pipelines , data lakes , and real-time data processing .
- Knowledge of scripting languages (Python, R) used in ML model development.
Contract Details :
- Duration : 1 year
- Location : Hybrid (3 days onsite in London)
- Start Date : ASAP
