Key Responsibilities
- Data Engineering & Pipelines
- Build and enhance data pipelines and automation workflows on Azure for large-scale data ingestion and processing
- Maintain and optimise existing toolkits, databases, dashboards, and API-based solutions
- Develop end-to-end automated data solutions across commodities (Gas/LNG, Power, Weather)
- Design and implement web scraping pipelines (e.g. US LNG data)
- Analytics & Real-Time Systems
- Support real-time and batch analytics use cases in a dynamic trading environment
- Enable and support analytics dashboards and GUI tools with reliable backend infrastructure
- Develop real-time flow tracking solutions at critical market points
- Data Modelling & Architecture
- Design and manage Snowflake data models, ensuring performance and scalability
- Integrate external data sources including ENTSOE, EPEX, KPLER, MetDesk, WoodMac, and others
- Collaborate with analytics teams to structure data for models and advanced analytics use cases
- Build and maintain data platforms supporting ML models such as demand forecasting
- Key Deliverables
- LNG Sendout Optimisation Model
- Ship Tracking & Flow Monitoring Tools
- Prompt Price & Forward Curve Bootstrapping
- Web scraping pipelines for US LNG and other market data sources
- Real-time flow tracking infrastructure at critical market points
- Data platforms supporting ML and demand forecasting models
Required Skills & Experience
- Technical
- Strong proficiency in Python for data engineering and pipeline development
- Hands‑on experience with Azure data services (Data Factory, Databricks, Blob Storage, etc.)
- Experience designing and optimising Snowflake data models
- Proven track record building and maintaining data pipelines at scale
- Experience integrating third‑party market data APIs and external data feeds
- Familiarity with SQL and data warehousing concepts
- Domain
- Experience or strong interest in energy, commodities, or financial markets data
- Understanding of real‑time and batch data processing patterns in a trading context
- Familiarity with market data providers such as ENTSOE, EPEX, KPLER, or similar
Nice to Have
- Experience with web scraping frameworks (e.g. Scrapy, BeautifulSoup, Playwright)
- Knowledge of LNG, Gas, or Power market fundamentals
- Experience supporting ML model pipelines or demand forecasting workflows
- Exposure to GUI/dashboard tools such as Grafana, Power BI, or Streamlit
- Knowledge of ship tracking data or AIS feeds
