At a Glance
- Tasks: Build and enhance data pipelines on Azure for large-scale data processing.
- Company: Join a leading energy firm focused on innovation and data-driven solutions.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on real-time analytics and market insights.
- Why this job: Make an impact in the energy sector while working with cutting-edge data technologies.
- Qualifications: Proficiency in Python and experience with Azure data services required.
The predicted salary is between 60000 - 80000 £ per year.
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.
- 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.
- 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.
Data Engineer employer: RocketFin Inc
As a Data Engineer at our company, you will thrive in a dynamic trading environment that values innovation and collaboration. We offer a supportive work culture that encourages professional growth through continuous learning opportunities and exposure to cutting-edge technologies on Azure. Located in a vibrant area, our team enjoys a flexible work-life balance and the chance to contribute to impactful projects in the energy and commodities sector.
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We think this is how you could land Data Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like RocketFin Inc!
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like RocketFin Inc.
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We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at RocketFin Inc, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at RocketFin Inc. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at RocketFin Inc
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at RocketFin Inc!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
