AWS Data Engineer - Pandas & Python

Role - AWS Data Engineer

Rate - £400-£575- Dependent on experience (Outside IR35)

Contract Length - Until the end of September then extensions

Location - Remote, 1 day in London a week would be much appreciated

Start Date - 7/8/2023



Role overview

The client I am working with is currently looking for an outstanding experienced Senior Data Engineer with an understanding of the data ecosystem to join a growing engineering team.

The ideal candidate is an experienced data pipeline builder and data wrangler, who enjoys writing Python code and translating from legacy R systems. The work is for a large-scale car manufacturer and involves building a brand-new platform in order to support advanced analytics. They will also enjoy using AI-accelerated tooling in order to empower their work but with an understanding of the nuances and pitfalls of said technologies.

The platform will be built in the AWS cloud, using tooling such as AWS Batch, S3, Athena, Glue, Python & Terraform, a good understanding of these is a must-have for any potential candidates.

About the client:

They are a team of data specialists who design, build, and embed cutting edge-data solutions that create value. By combining in-house expertise with an extensive network of specialist and academic partnerships, they help clients become more efficient and more effective through data.

Key responsibilities and skills

* Strong project management and organisational skills, with the ability to prioritise and meet deadlines in a calm and effective way.
* Work with technical partners and suppliers to ensure their technology is implemented for our internal requirements and for our client projects.
* Be heavily involved in the building and development of the architecture and engineering process of projects including building APIs as well as other scripts to set up and automate engineering pipelines and solutions.
* Create, automate and maintain optimal data pipeline architecture.
* Worked extensively in building scalable and high-performing code, fit for production.
* Strong Python programmer. In-depth knowledge and expertise in data transformation and manipulation techniques in Python, including libraries such as Pandas and Numpy
* R knowledge is highly desirable
* Familiarity with deploying and managing machine learning models in a production environment is highly desirable

Regards

Ollie