Data Engineer

RocketFin Consulting Ltd
London, UK
about 2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Data Analysis Microsoft Azure Big Data Databases Information Engineering Web Scraping Data Systems Data Warehousing Python (Programming Language) Machine Learning Power BI
+13 more
SQL Databases Data Processing Real Time Systems Azure Data Factory Snowflake Grafana Backend Playwright Data Management Api Design Streamlit Framework Data Pipelines Databricks

Job description

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

Requirements

Do you have experience in SQL?, 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, * 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

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on indeed.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:09 min

Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

1:52 min

Structuring and scaling the backend engineering team

Stefan Lingler Stefan Lingler +1 · Coffee With Developers

10:40 min

Visualizing Prometheus open metrics using custom Grafana dashboards

Stijn Polfliet · LIVE

3:28 min

Defining big data and machine learning fundamentals

Ayon Roy · LIVE

56 sec

Introduction to analytical data formats for software developers

Matthias Niehoff Matthias Niehoff · World Congress 2026 Europe

1:12 min

Choosing TypeScript for complex backend applications

Maximilian Otto Maximilian Otto · World Congress 2024

Videos

See all

Related articles

See all