Global Manager, Data Engineering

~ TrailStone is a global energy trader and risk manager. Our mission is to play a leading role in facilitating the worldwide transition to renewable power. ~

Our primary business is real-time management of electricity generation assets. Our team of traders, meteorologists, software engineers, risk managers, and data scientists aim to increase the stability of electric grids while minimizing risk for generators of intermittent electricity from wind and solar investments. TrailStone leverages its energy market experience and predictive modelling platform to take and manage financial trading risk in energy markets.

TrailStone operates and develops a platform to trade renewable electricity assets like wind and solar power plants in Europe and North America. Today our Robotic, AI & ML-driven real-time order execution manages thousands of renewable electricity assets.

At TrailStone we believe in shared success for our investors and our employees. Success is driven by exceptional people working together as a team with a passion for the mission and common values.

What is the role?

The Global Manager, Data Engineering is a leadership role in TrailStone. You will be responsible for evolving our Data Engineering strategy towards the frontier, incorporating modern practices. Additionally, you will be responsible for growing and leading a team with a diverse skillset. You are also expected to work alongside your team, we are all “player-coaches” at TrailStone.

You must have strong, hands-on technical expertise in a variety of technologies including Python, SQL Server, AWS Aurora, Docker as well as the proven ability to fashion robust, scalable solutions for our clients.

What will you do?

• Lead large scale projects that integrate our data and machine learning applications into trading applications
• Act as a player/coach hiring for and leading a team of data engineers as well as providing thought leadership and leading best practice solutions for the team.
• Take lead in driving a culture of high quality, innovation, and incremental experimentation.
• Has a knack of using flexible and scalable methodologies that can be applied to a broad set of problems across the Data Engineering organization.
• Provide strong thought leadership and set processes that lead to good implementation architecture.
• Continuously improve and further enhance existing ETL and streaming systems

What do you need?

• Significant experience working in formal engineering environments and deep experience working on and leading large-scale data projects
• Significant team management experience
• Knowledge about how to automate ETL with scheduling systems, e.g., Airflow, etc.
• Extensive working knowledge of Python
• Expert level knowledge of SQL, including performance tuning for large datasets
• Deep understanding about technical debt in data systems
• Extensive experience in designing and implementing large scale data projects from basic requirements
• Extensive experience in maintaining key data systems over long periods of time
• BS or MS degree in Computer Science, Math, Statistics or a related technical field
• Commodities, Fixed Income, or Equities Trading experience, a plus