At a Glance
- Tasks: Design and build data processing pipelines using cutting-edge tech to handle terabytes of data.
- Company: Vortexa, a fast-growing tech company revolutionising the energy industry with AI.
- Benefits: Flexible working, private health insurance, equity options, and a vibrant team culture.
- Other info: Collaborative environment with opportunities for personal growth and continuous learning.
- Why this job: Join a dynamic startup and make a real impact in the energy sector with innovative solutions.
- Qualifications: Experience in AWS, K8s, Python, and Java; strong software engineering fundamentals.
The predicted salary is between 48000 - 84000 £ per year.
Vortexa is a fast‑growing international technology business founded to solve the immense information gap that exists in the energy industry. By using massive amounts of new satellite data and pioneering work in artificial intelligence, Vortexa creates an unprecedented view on the global seaborne energy flows in real‑time, bringing transparency and efficiency to the energy markets and society as a whole.
Role
Processing thousands of rich data points per second from many and vastly different external sources, moving terabytes of data while processing it in real‑time, running complex prediction and forecasting AI models while coupling their output into a hybrid human‑machine data refinement process and presenting the result through a nimble low‑latency SaaS solution used by customers around the globe is no small feat of science and engineering. This processing requires models that can survive the scrutiny of industry experts, data analysts and traders, with the performance, stability, latency and agility a fast‑moving startup influencing multi‑$m transactions requires.
The Data Production Team is responsible for all of Vortexa's data. It ranges from mixing raw satellite data from 600,000 vessels with rich but incomplete text data, to generating high‑value forecasts such as the vessel destination, cargo onboard, ship‑to‑ship transfer detection, dark vessels, congestion, future prices, etc.
The team has built a variety of procedural, statistical and machine learning models that enabled us to provide the most accurate and comprehensive view of energy flows. We take pride in applying cutting‑edge research to real‑world problems in a robust, long‑lasting and maintainable way. The quality of our data is continuously benchmarked and assessed by experienced in‑house market and data analysts to ensure the quality of our predictions.
You'll be instrumental in designing and building infrastructure and applications to propel the design, deployment, and benchmarking of existing and new pipelines and ML models. Working with software and data engineers, data scientists and market analysts, you'll help bridge the gap between scientific experiments and commercial products by ensuring 100% uptime and bullet‑proof fault‑tolerance of every component of the team's data pipelines.
Qualifications
- Experienced in building and deploying distributed scalable backend data processing pipelines that can go through terabytes of data daily using AWS, K8s, and Airflow.
- With solid software engineering fundamentals, fluent in both Java and Python (with Rust good to have).
- Knowledgeable about data lake systems like Athena, and big data storage formats like Parquet, HDF5, ORC, with a focus on data ingestion.
- Driven by working in an intellectually engaging environment with the top minds in the industry, where constructive and friendly challenges and debates are encouraged, not avoided.
- Excited about working in a start‑up environment: not afraid of challenges, excited to bring new ideas to production, and a positive can‑do will‑do person, not afraid to push the boundaries of your job role.
- Passionate about coaching developers, helping them improve their skills and grow their careers.
- Deep experience of the full software development life cycle (SDLC), including technical design, coding standards, code review, source control, build, test, deploy, and operations.
Preferred Skills
- Have experience with Apache Kafka and streaming frameworks, e.g., Flink.
- Familiar with observability principles such as logging, monitoring, and tracing.
- Have experience with web scraping technologies and information extraction.
- A vibrant, diverse company pushing ourselves and the technology to deliver beyond the cutting edge.
- A team of motivated characters and top minds striving to be the best at what we do at all times.
- Constantly learning and exploring new tools and technologies.
- Acting as company owners (all Vortexa staff have equity options) – in a business‑savvy and responsible way.
- Motivated by being collaborative, working and achieving together.
- A flexible working policy – accommodating both remote & home working, with regular staff events.
- Private Health Insurance offered via Vitality to help you look after your physical health.
- Global Volunteering Policy to help you 'do good' and feel better.
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Data Engineer (Multiple Roles) - AI SaaS in City of London employer: Vortexa
Vortexa is an exceptional employer located in the heart of Greater London, offering a dynamic hybrid work environment that fosters collaboration and innovation. With a strong emphasis on employee growth and personal development, team members are encouraged to take on new challenges and drive impactful business initiatives. The vibrant company culture not only values individual contributions but also promotes a sense of community, making it a rewarding place for those looking to make a meaningful impact in the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (Multiple Roles) - AI SaaS in City of London
✨Get Involved in Data Science Meetups
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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 Vortexa.
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When you find a suitable opening like Data Engineer (Multiple Roles) - AI SaaS at Vortexa, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Engineer (Multiple Roles) - AI SaaS in City of London
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 Vortexa, 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 Vortexa. 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 Vortexa
✨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 Vortexa!
✨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.