Role Overview
We operate a hybrid model where brokers provide business-critical intelligence to clients. It’s supplemented by proprietary screens for historical data, analytics and execution functionality. Globally, we’re the leading provider of proprietary over the counter pricing information and a unique source of data on financial, energy and commodities products. Our market data is independent, unbiased and non-position influenced. Our clients include banks, insurance companies, pension and hedge funds, asset managers, energy producers and refiners as well as risk and compliance managers and charities.
We are looking for a passionate and capable Data Engineer who wants to make a real impact and build software they can be proud of. We work in a collaborative, fast paced environment where you will design, build and deploy new systems and products.
Role Responsibilities
Building performant batch and streaming data pipelines.
Building GenAI driven data products.
Data warehouse development.
Cloud based development.
Improving CI/CD Processes.
Maintaining data applications, pipelines and databases.
Participating in daily stand ups and agile development teams.
Writing unit, integration and data quality tests.
Contributing to documentation and best practice guidelines.
Staying up to date with current technology and techniques.
Experience / Competences
Essential
Bachelor's degree in computer science, engineering, mathematics, or a related technical discipline.
Experience working with Python and SQL, other languages like Java, C# or C++ are also useful.
Experience with time-series market data is desirable.
Able to write clean, scalable and performant code.
Proven written and verbal communication skills including an ability to effectively communicate with both business and technical teams.
Desired
Some knowledge of Linux and the command line.
Understanding of ETL and event streaming e.g. Kafka.
Snowflake, Kubernetes and Airflow experience is desirable.
Experience with Amazon Web Services (AWS) would be beneficial.
Basic knowledge of data science topics like machine learning, data mining, statistics, and visualisation.
#PARAMETA #LI-Hybrid #LI-MID
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ResponsibilitiesBuilding performant batch and streaming data pipelines. Building GenAI driven data products. Data warehouse development. Cloud based development. Improving CI/CD Processes. Maintaining data applications, pipelines and databases. Participating in daily stand ups and agile development teams. Writing unit, integration and data quality tests. Contributing to documentation and best practice guidelines....
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