Data Engineer

Zuhlke Engineering Ltd | London

Date listed

1 month ago

Employment Type

Full time

Glassdoor Rating

4/5 (58 reviews)

About Us

Zuhlke Engineering is an international consultancy that helps companies achieve success by turning ideas into real-life results. To do this, we provide interdisciplinary teams, currently across Europe and Asia, to work closely with our customers to deliver solutions. In the UK, we support digital innovation and embedded software. Across the group, we cover digital systems, Internet-connected devices, and physical product design (embedded and mechatronics).   

Our clients range from the largest multinationals to start-ups: what they have in common is the need for a partner who can be trusted to deliver effectively.  

Your job will involve working in small teams, communicating closely with our clients to design, develop, test, and ship systems that deliver value. You will be looking both to contribute to the company and to grow personally.  

Our reputation is fundamental to our business, so our culture emphasizes quality, reliability and respect. As a privately-held company owned by past and present employees, and run by engineers, Zuhlke takes a long-term view. For example, you will receive twenty days training per year including a budget to support activities such as conference attendance, our annual technical camp, and participation in focused technical subject teams. We expect our staff to be flexible so we will support you learning any required skills you don't have now.  

As part of our longer-term view, we believe that diversity in the workplace benefits all, we have ethical guidelines about which client industries we will work for, and we have an initiative to become carbon neutral during 2020.  

Your job will include:

  • As a Data Engineer you master the big data world and help our customers to make their own data fit for business or operational purpose - whether in the Cloud or in their own data centre.
  • You develop, test and monitor distributed data processing pipelines.
  • You work closely with data scientists on the development of machine learning models.
  • You extrapolate versatile data sets and sources in a performant and repeatable way.
  • You prepare performance and cost estimates for various use cases.
  • You develop and create compelling dashboards to visualize the processed data.
  • You work collaboratively with colleagues and clients, be it onsite, in the Zuhlke office, or from home.
  • You keep yourself technically sharp and get things done.
  • You occasionally travel to other Zuhlke locations, e.g. in mainland Europe, for project work or for developing competencies across the Zuhlke group.

Skills & Requirements:

  • You have a degree in computer science or mathematics, or a comparable qualification.
  • You have a rich experience of professional data engineering experience, implementing projects in industry and services, ideally in client facing contexts.
  • You are familiar with big data infrastructures (e.g. Hadoop/Spark ecosystem) and concepts for storing and processing large and/or heterogeneous data volumes.
  • You have practical knowledge of handling varied types of data (text, tabular, graph, time-series, geospatial, image, etc.).
  • You have excellent programming skills in Python, Java and SQL as well as hands-on experience with databases (relational/NoSQL), containerisation, and Cloud environments such as AWS or GCP.
  • You are familiar with business intelligence, data analytics and data visualisation frameworks.
  • Information security knowledge is a plus.

Our work is mainly at or within an hour's travel from our London office.  

If you're interested in joining us, send us your CV and start your first step into realising your career goals at a company that values talent and cares about its employees.  We are an  equal opportunity  employer and  value diversity  at our company. 

We welcome people from all backgrounds, regardless of their gender, personality, national origin, race, religion, colour, sexual orientation, gender identity, age, marital status, disability or veteran status.



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