Software Engineer- Python

Vortexa

Greater London

On-site

GBP 30,000 - 40,000

Full time

14 days+

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Benefits offered by this job

Private Health Insurance

Global Volunteering Policy

Equity options

Job summary

A fast-growing international technology company based in the UK is seeking an entry-level engineer to design and build infrastructure for data pipelines. The role involves collaboration with software engineers and data scientists to ensure robust, 100% uptime data processes. Ideal candidates will be fluent in Python and have a strong understanding of distributed systems and micro-service architectures. The company offers a full-time position with opportunities for professional growth and development.

Qualifications

Experience building systems that process terabytes of data daily.
Deep experience of the full software development life cycle (SDLC).
Comfortable with highly scalable data processing libraries.

Responsibilities

Design, build, operate and benchmark infrastructure for data pipelines.
Collaborate with engineers and analysts to deliver solutions.
Ensure 100% uptime and fault-tolerance for data pipeline components.

Skills

Fluent in Python

Distributed systems

Micro-service architectures

Scalable data processing pipelines

Coaching developers

Tools

AWS

Apache Kafka

Kubernetes

Job description

About Vortexa

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.

Processing thousands of rich data points per second from many 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 Platform Team is responsible for all of Vortexa's data. The team's ownership ranges from raw satellite AIS/imaging data to unstructured textual and graphical maritime data like fixtures, port lineups, and customs filings. The team is also responsible for highly structured datasets such as price and supply‑demand forecasts as well as modeling the global energy flows and tanker fleet distributions.

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.

About the Role

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.

Key Responsibilities

Design, build, operate and benchmark infrastructure and applications for data pipelines and ML models.
Collaborate with software, data engineers, data scientists and market analysts to deliver production‑ready solutions.
Ensure 100% uptime and fault‑tolerance for all data pipeline components.

Requirements

Fluent in Python and software engineering fundamentals, comfortable with highly scalable data processing libraries.
Strong expertise in distributed systems, micro‑service architectures and scalable data processing pipelines.
Experience building distributed heavy‑load backend systems that process terabytes of data daily.
Deep experience of the full software development life cycle (SDLC), including technical design, coding standards, code review, source control, build, test, deploy, and operations.
Passionate about coaching developers, helping them improve their skills and grow their careers.

Nice to Have

Experience in Rust / Java / Kotlin.
Experience with AWS, Apache Kafka, Kafka Streams, Apache Beam / Flink / Spark, deployment, monitoring & debugging.
Productisation of Machine Learning research projects.
Familiarity with Airflow or other workflow orchestration tools, Kubernetes.
Knowledge of data lake systems and file formats like Parquet, Orc, Athena.
Relevant AWS or Kafka certifications.
Team‑oriented mindset, motivated to collaborate and achieve together.
Flexibility for remote & home working; participation in regular staff events.
Private Health Insurance offered via Vitality.
Global Volunteering Policy.
Acting as company owners with equity options in a business‑savvy manner.