Building the future of energy markets
Vortexa tracks more than $3 trillion of waterborne energy trades per year in real-time, providing energy and shipping companies with the most complete picture…
Building the future of energy markets
Vortexa tracks more than $3 trillion of waterborne energy trades per year in real-time, providing energy and shipping companies with the most complete picture…
Product: Real-time energy and freight analytics platform for crude, refined products, LPG and LNG
Tech: Vessel-tracking, market data and machine learning models
Founding year: 2016
Founders: Fabio Kuhn and Etienne Amic
Recent financing: Series C $34M (Jan 2024) and debt financing Oct 2024
Company Overview
Problem Domain
Energy market intelligence and freight analytics for trading and chartering decisions.
Founded
2016
Industry
Software Development
Funding Track Record
Series C- January 8, 2024
$34M
Debt Financing- October 22, 2024
Debt financing reported in Oct 2024
Investor Signal
“Backers include Morgan Stanley Expansion Capital, Notion Capital, monashees and others”
Founders
What we do
Join the Team
Data Engineer
On-SiteLondon, GB
On-Site • London, GB
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Who you are
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
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
What the job involves
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
Benefits
A flexible working policy - accommodating both remote and home working, with regular staff events
Workplace Pension Scheme via The People's Pension
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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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 bulletproof fault-tolerance of every component of the team's data pipelines
