Data Architect - Energy Modeling

London
1 month ago
Applications closed

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The Role: Data Architect

Location: London, UK

Position Type: Contract Inside IR35

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 (e.g., 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

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