RocketFin Consulting Ltd
Data Engineer

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### **Position Title** *[Not explicitly stated; role likely focused on **Data Engineer** or **Senior Data Engineer** in an energy/trading analytics context]*
## **Key Responsibilities**
### **Data Engineering & Pipelines**
- Build and enhance **data pipelines** and **automation workflows** on **Azure**, focusing on 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**, e.g., **demand forecasting**
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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


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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 ENTSO-E, 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
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