Senior Data Engineer (Python, PySpark) - Remote
Our client is a global innovator and world leader with one of the most recognisable names within technology. They are looking for a Senior Data Engineer with significant Python and PySpark experience to join an exceptional Agile engineering team and work on enterprise-grade software systems using Databricks, Python, Spark, R, and SQL.
We are seeking a Senior Data Engineer capable of providing input on best practices and development standards, and mentoring other team members. The role will include working with architects, creating automated tests, instilling a culture of continuous improvement, and setting standards for the team. You will be responsible for building a greenfield modern data platform using cutting-edge technologies, driving innovation, defining data platform stacks, and contributing to the great company culture.
The successful candidate will have strong Python, PySpark, and SQL experience, possess a clear understanding of Databricks, as well as a passion for Data Science (R, Machine Learning, and AI). Database experience with SQL and No-SQL (Aurora, MS SQL Server, MySQL) is expected, as well as significant C#, Agile, and Scrum exposure along with SOLID principles. Continuous Integration tools, Infrastructure as code, and strong Cloud Platform knowledge, ideally with AWS, is also key.
This is a truly amazing opportunity to work for a prestigious brand that will do wonders for your career. They invest heavily in training and career development with unlimited career progression for top performers.
Location: Remote
Salary: £55k - £75k + Bonus + Pension + Benefits
To apply for this position please send your CV to Nathan Warner at Noir Consulting.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.