Software​/Data Engineer

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Salary: Up to £50,000 p/a (depending on skills and experience) plus staff share of profit and excellent benefits.

Job type: Permanent and Full Time (35 hours p/w)

Reporting to: Head of Engineering

Location: Edinburgh, Scotland - Hybrid working

We support people to work from wherever they are most comfortable, but we understand the importance of coming together to collaborate, socialise and build relationships, so our jobs are all part of a hybrid working approach.

ABOUT GOOD-LOOP

Good-Loop makes it easy and profitable for big brands to do good  mission is to create a positive role for advertising in society and we do that by building products that help brands plan, measure and buy Good-Media. They’re ads, except they’re good.

We work with the biggest brands in the world, from Nike and Adidas to L’Oreal, Doritos, Nature Valley and Toyota to deliver attention-earning, sustainable ads that prove doing good is good for business. And our carbon-neutral advertising has raised over $11m for good causes around the world – all while supporting quality journalism and diverse publications.

As the first carbon neutral B Corp in AdTech, Good-Loop is uniquely positioned to capitalise on the increasing consumer demand for businesses to step up and contribute to society. We’re a small, but agile and fast-moving team with a lot of heart and even more ambition.

ABOUT THE ROLE

As a Data Engineer with AI Experience, you will play a key role in designing, developing, and optimising scalable data pipelines and infrastructure. You will collaborate with data scientists, AI engineers, and cross-functional teams to integrate AI models into production environments while ensuring data integrity, security, and efficiency.

Responsibilities:

• Design, implement, and maintain scalable data pipelines and infrastructure.
• Develop data ingestion processes from various sources, ensuring reliability and efficiency.
• Collaborate with cross-functional teams to understand data and AI model requirements and deliver robust solutions.
• Optimise data pipelines for performance, reliability, and scalability.
• Ensure data quality and integrity through validation and monitoring processes.
• Implement data security and privacy measures to protect sensitive information.
• Build and deploy machine learning pipelines and support AI-driven applications.
• Collaborate with data scientists and AI engineers to ensure seamless integration of AI models into production environments.
• Stay updated with emerging technologies and best practices in data engineering and AI.

Experience:

• Experience in designing and building data pipelines and infrastructure.
• Proficiency in programming languages such as Python, Java, or Scala.
• Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud.
• Strong understanding of database technologies, SQL, and No
  
  SQL databases.
• Experience working with AI frameworks and libraries such as Tensor Flow, PyTorch, or Scikit-learn.
• Familiarity with building and deploying machine learning models in production environments.
• Excellent problem-solving skills and ability to troubleshoot complex data and AI-related issues.
• Strong communication and collaboration skills.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• Knowledge of MLOps practices, including model monitoring and versioning.

Key Performance Indicators (KPIs):

• Timely delivery of scalable data and AI-driven solutions.
• Data pipeline performance and reliability metrics.
• Data quality metrics and resolution of data issues.
• Implementation of data security and privacy measures.
• Successful deployment and performance of AI models in production.
• Efficiency and scalability of AI model inference pipelines.
• Contribution to team knowledge and adoption of best practices.

Research shows that while men apply for jobs when they meet an average of 60% of the criteria, women and other marginalised groups tend to only apply when they tick every box. So if you think you have what it takes, but don’t necessarily meet every single requirement on the list above, please still get in touch. We’d love to have a chat and hear about what else you…