Location: London (2-3 days/week)
Salary: £80,000 - £100,000 + Bonus DOE
The Green Recruitment Company are delighted to be working with one of the biggest renewable energy producers and solutions providers in Europe in their search for a skilled Senior Data Engineer/Data Manager to play a significant role in their digitalisation and data-centric growth.
As a key member of the Trading Software team, you would have the exciting opportunity to develop an original framework that enables the Origination & Trading team to meet their strategic goals – using large-scale data sets.
This individual would be providing data handling & development expertise to a range of internal teams (including traders and analysts), so experience and a proven ability to work with large-scale data in commodity/energy trading markets is essential - ideally using Python.
Ensuring the Origination & Trading (O&T) team’s data sets are genuine and accurate and create new processes of data testing as required.
Execute effective and secure procedures for data handling and analysis and provide support to internal teams when data sets are missing or incorrect.
Employ best practices when organising and cleaning data and report any missing data.
Analyse data systems and assets for O&T and assess performance, suggesting ways to become more effective.
Oversee O&T’s existing data sets and procedures.
Analyse end-user requirements, ensuring their needs are met.
Co-ordinate, prioritize and ensure operationalization of data to production systems as and when required.
Collaborate with Data Vendor Management regarding data sourcing, extraction and reporting as needed.
Ensure data usage and management protocols are within legal and company requirements.
Python expertise (data-related packages such as pandas & NumPy is a big plus).
Experience working in commodity/energy trading markets.
Proven ability to manage and store large-scale data in commodity/energy trading markets.
Programming experience in Spark, SQL, and API development.
Strong data pipeline engineering skills & Database Architecture understanding.
Relevant academic background – within a STEM, analytical, or financial subject.
Ability to collaborate across different functions and communicate effectively.