Data Architect - Energy Modeling
Posted 5 days ago by Vallum
Negotiable
Inside
Hybrid
London, UK
Summary: The Data Architect role focuses on designing and managing data systems for energy modeling, ensuring data accessibility and reliability for analysis. This position requires expertise in integrating diverse data sources and optimizing data pipelines within the energy sector. The role involves collaboration with domain experts to translate business needs into technical specifications. It is a contract position based in London, UK, with a hybrid working arrangement.
Key Responsibilities:
- Data Architecture
- Data modelling
- Flexibility Energy Market, energy modelling etc.
- Create conceptual, logical, and physical data models for energy systems
- Integrate data from varied sources into a unified data lake or mesh
- Design and implement automated ETL/ELT processes
- Define and enforce standards for metadata, data quality, and master data management
- Optimize databases and storage solutions for fast data retrieval
- Implement security measures to protect sensitive operational data
- Collaborate with energy engineers, analysts, and stakeholders
- Utilize industry-standard models for grid operations
- Structure data for building energy modeling
- Integrate data from renewable assets for predictive maintenance
Key Skills:
- Strong proficiency in SQL, NoSQL, and big data technologies (Spark, Kafka, Hadoop)
- Experience with AWS, Azure, or Google Cloud
- Proficiency in Python or Scala for data manipulation
- Knowledge of energy markets, utility operations, or building simulation software
- 8-15+ years of experience in data engineering or architecture
- Bachelor's or master's degree in Computer Science or Engineering
Salary (Rate): undetermined
City: London
Country: UK
Working Arrangements: hybrid
IR35 Status: inside IR35
Seniority Level: undetermined
Industry: IT
The Role: Data Architect
Location: London, UK
Position Type: Contract Inside IR35
Implementation Partner -Elexon
Remote work option Available: Hybrid - 2 Days Onsite
Job Description:
- Data Architecture
- Data modelling
- Flexibility Energy Market, energy modelling etc.,
An Energy Modelling Data Architect is a specialized role responsible for designing, structuring, and managing the data systems used to simulate, analyze, and optimize energy consumption, production, and distribution. They bridge the gap between complex energy engineering models (eg, HVAC, solar, grid) and IT infrastructure, ensuring data is accessible, reliable, and secure for analysis.
Core Roles and Responsibilities
Data Modeling & Architecture Design: Create conceptual, logical, and physical data models for energy systems, including time-series data from IoT sensors, smart meters, and SCADA systems.
Integration of Disparate Sources: Integrate data from varied sources such as building automation systems, utility market data, and energy performance platforms into a unified data lake or mesh.
Pipeline Development (ETL/ELT): Design and implement automated extraction, transformation, and loading (ETL/ELT) processes to move, clean, and format data for analysis.
Data Governance & Quality: Define and enforce standards for metadata, data quality, data lineage, and master data management to ensure accuracy in simulation results.
Performance Optimization: Optimize databases and storage solutions to ensure fast retrieval of large-scale, high-frequency energy data.
Security & Compliance: Implement security measures (masking, encryption, access controls) to protect sensitive operational data, adhering to regulations like GDPR.
Collaboration with Domain Experts: Work with energy engineers, analysts, and stakeholders to translate business requirements into technical specifications.
Specific Energy Industry Context
Smart Grid/Utility Integration: Utilize industry-standard models such as CIM (Common Information Model) or CGMES (Common Grid Model Exchange Standard) for grid operations.
Building Energy Modeling (BEM): Structure data relating to building geometry, mechanical/electrical systems, and environmental factors to support ASHRAE 209 cycles.
Renewable & Asset Management: Integrate data from geothermal, solar, or wind assets to support predictive maintenance and performance analytics.
Key Skills and Qualifications
Technical Expertise: Strong proficiency in SQL, NoSQL, and big data technologies (Spark, Kafka, Hadoop).
Cloud Platforms: Experience with AWS (Glue, S3, Redshift), Azure (Data Factory, Synapse), or Google Cloud.
Languages: Proficiency in Python or Scala for data manipulation.
Domain Knowledge: Knowledge of energy markets, utility operations, or building simulation software.
Experience: Typically requires 8-15+ years of experience in data engineering or architecture, often with a bachelor's or master's degree in Computer Science or Engineering.