Careers

Data Engineer

10th Mar 2021 / 17:54

Location: Flexible location
Type: Full Time, Permanent
Salary: Dependent on Experience

Netacea provides a revolutionary bot management solution that protects websites, mobile apps and APIs from malicious attacks such as scraping, credential stuffing and account takeover. We have developed our own cutting edge machine learning algorithms to solve real time feedback on huge unlabelled data sets.

We are looking for a Data Engineer to work within the Data Science team to ensure best practise is followed in data and model management and providing a stable, scalable platform.

Responsibilities

We are looking for a someone who is passionate about technology, data and building a stable, scalable platform. The Data Science team has a broad responsibility for developing Netacea’s analytics and Machine Learning capabilities, together we;

  • Effectively analyse and understand large, complex datasets
  • Explore new business/data problems through the application of statistical methods and machine learning
  • Drive solutions from research, through prototype and into production to directly contribute to the Netacea product
  • Collaborate with other areas of the business to ensure we’re always producing high quality, high impact solutions
  • Keep up to date with latest developments in ML/Deep Learning/Data Science
  • Champion Data Science principles throughout the wider business

The Data Engineer role will focus on ensuring the Data Science infrastructure supports development work within the team as well as serving our customers needs. They will work closely with the other technical teams, representing Data Science.

Skills & Competencies

As part of the Data Science team at Netacea you will not be expected to know everything or be an expert in all facets of the job. You will be working as part of a team whose collective knowledge and experience add together to provide true value to the company. You will be supported in your learning through, mentorship, training and freedom to experiment.

Essential

  • A strong programming ability, particularly experience with Python
  • Understanding of software development best practice and workflows
  • Experience with big data tools such as Spark
  • Understanding of the ML model lifecycle
  • A strong data background, comfortable with large real time datasets
  • An understanding of common ML approaches, when to use them and how to assess performance
  • Excellent communication and collaboration
  • A strong desire to learn

Desirable

  • Experience with Data Lake technologies
  • Familiar with the DataBricks environment and integrated tools such as Delta Tables and MLFlow
  • Experience with scheduling tools such as Airflow
  • Experience with Kafka
  • Low level network knowledge such as understanding of HTTP protocols
  • Weblog analysis experience

 

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