Data Engineer

Data Engineer

Glasgow Full-Time 60000 - 75000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Join our team as a Data Engineer, building impactful data infrastructure for climate solutions.
  • Company: Climate Policy Radar is a not-for-profit startup focused on making climate documents accessible and understandable.
  • Benefits: Enjoy a 4-day workweek, unlimited leave, and a vibrant, collaborative culture.
  • Why this job: Be part of a mission-driven team at the forefront of AI and climate action.
  • Qualifications: Experience in Python, data modelling, MLOps, and cloud infrastructure is essential.
  • Other info: We welcome diverse applicants and offer a clear, inclusive recruitment process.

The predicted salary is between 60000 - 75000 £ per year.

Climate Policy Radar is on a mission to help people access and understand long climate documents. Nearly 350,000 users from over 100 countries already use our open databases and AI-based research tools to search through 500,000+ pages of climate documents from around the world. We care deeply about creating trustworthy tools that have a real impact on climate decisions.

We are a not-for-profit startup, with a team of ~30 technologists and climate policy experts who care a lot about the ‘how’ (our values and culture) as well as the ‘what’. As part of that, we have embraced a flexible, hybrid approach to work, including a 4 day workweek.

Role Overview: We are looking for a Data Engineer to join our Platform team. Working with the existing team of three engineers and collaborating with the data science and application teams. In this role, you will help build and improve the data and machine learning infrastructure supporting our R&D and production platforms of high-impact tools and products for global climate law and policy.

Some examples of what you will work on:

  • Pipelines for training and deploying bespoke classifiers for identifying structure in our unstructured document datasets
  • Building out the infrastructure to serve our knowledge graph at scale across our product portfolio
  • Productionising our generative AI workstreams to support deploying and leveraging open source large language models
  • Building infrastructure and tooling for enabling internal teams, by scaling our data infrastructure, optimizing for reliability and cost, or improving our search service

Tech Stack:

  • Platform: AWS, Pulumi, Docker, Prefect, Github actions, Grafana cloud monitoring
  • Data Science: Python, PyTorch, Pandas, Spacy, Huggingface, Numpy, Streamlit, Argilla, Weights and Biases
  • Backend: Python, FastAPI, PostgreSQL, Vespa, SQLAlchemy, AWS Batch, Lambda, S3
  • Frontend: React, Next.js

Key skills and experience:

  • Experience using Python
  • Experience with data modelling, and building data infrastructure
  • Experienced in MLOps and building scalable data pipelines for ingestion and document processing
  • Experience in at least one area of data science we work on: knowledge graphs, information retrieval, text classification, generative AI
  • Experience working with machine learning models in production systems
  • Experience using and maintaining cloud infrastructure
  • Experience with DevOps/infrastructure/SRE, tools used for automation, CI/CD, infra-as-code, containerisation, orchestration
  • Experience with system design, working on system architecture or making technical decisions, whether individually or with a team
  • Extensive knowledge of different data stores, and formats
  • Solid understanding of software engineering fundamentals, version control, observability, unit and integration testing

Our ideal candidate will champion engineering excellence, open source, enabling internal users and creating delightful user experiences. We are looking for candidates with significant experience in highly collaborative cross-functional teams, excitement about working in a startup/scaleup environment and all that brings. We are a mission driven organisation, and work best with people who have strong alignment with our values.

We actively encourage applicants from diverse and historically underrepresented backgrounds. Not sure if you tick all the boxes but feel like you align with our values, are excited about working in Climate Change and AI and have the potential to do well in the role? Click apply! We’d love to hear from you.

Salary and Benefits:

  • Salary: Up to £75k pa DOE
  • A deep commitment to employee wellbeing, including policies such as 4 day workweek (same pay, Fridays off), unlimited annual leave, and a wellbeing allowance
  • A vibrant, collaborative, empathetic work culture that thrives on innovation and the impact of our work
  • Either remote working or in a hybrid work environment (2 days a week) in London’s leading climate tech hub

Interview process: We know that applying for a new job can be full of uncertainties - and we aim to reduce those by communicating clearly. Our process is made of several stages. After each stage, we’ll contact you as soon as we can and no longer than 2 working days, to let you know if you will be progressing to the next stage.

We also ensure all applicants are assessed fairly through structured interviews and diverse hiring panels. We are committed to making our recruitment process inclusive and accessible. If you require any accommodations due to a disability or specific need, please contact us.

Process:

  • 1 hour behavioural interview with the Chief Technical Officer and one other team member
  • 1.5 hour interview with two team members, consisting of a paired technical assessment
  • 1 hour system design interview with two team members (senior only)
  • 30 minutes values fit interview with CEO and Head of People (in person)
  • Opportunity to chat to other team members (this is not an interview, but gives you the opportunity to get to know the team and learn more about us in an informal setting)
  • Offer subject to references

Right to Work in the UK: Unfortunately, we are currently unable to sponsor work visas. Only applicants legally authorised to work in the UK will be considered.

Equal opportunities: At Climate Policy Radar, we are committed to fostering a workplace that is inclusive and equitable. Climate Policy Radar welcomes applicants from all backgrounds and does not tolerate discrimination in any aspect of employment.

Data Engineer employer: Climate Policy Radar

At Climate Policy Radar, we pride ourselves on being an exceptional employer, offering a vibrant and collaborative work culture that prioritises employee wellbeing with a 4-day workweek and unlimited leave. Our London-based team thrives at the forefront of climate action and AI innovation, providing unique opportunities for professional growth while making a meaningful impact on global climate policy. Join us in our mission-driven environment where your contributions will help shape the future of climate understanding and decision-making.
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Contact Detail:

Climate Policy Radar Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Engineer

✨Tip Number 1

Familiarise yourself with the specific tech stack mentioned in the job description, especially AWS, Python, and MLOps tools. Being able to discuss your experience with these technologies during the interview will show that you're a strong fit for the role.

✨Tip Number 2

Highlight any previous experience you have working in collaborative, cross-functional teams. Since the role involves working closely with data science and application teams, demonstrating your ability to work well with others will be crucial.

✨Tip Number 3

Prepare to discuss your understanding of climate change and its relevance to the role. Showing genuine interest in the mission of Climate Policy Radar can set you apart from other candidates who may not share the same passion.

✨Tip Number 4

Be ready to talk about your experience with system design and architecture. The role requires making technical decisions, so showcasing your problem-solving skills and thought process in this area will be beneficial during the interviews.

We think you need these skills to ace Data Engineer

Proficiency in Python
Data Modelling
Building Data Infrastructure
MLOps Experience
Scalable Data Pipeline Development
Knowledge Graphs
Information Retrieval
Text Classification
Generative AI
Machine Learning Model Deployment
Cloud Infrastructure Management
DevOps Tools and Automation
CI/CD Practices
Infrastructure as Code
Containerisation and Orchestration
System Design and Architecture
Version Control Systems
Observability and Monitoring
Unit and Integration Testing

Some tips for your application 🫡

Tailor Your CV: Make sure to customise your CV to highlight relevant experience in data engineering, Python programming, and MLOps. Emphasise any projects or roles that align with the job description provided by Climate Policy Radar.

Craft a Compelling Cover Letter: Write a cover letter that not only showcases your technical skills but also reflects your passion for climate change and AI. Mention how your values align with those of Climate Policy Radar and why you want to be part of their mission.

Showcase Relevant Projects: Include specific examples of past projects where you built data pipelines, worked with machine learning models, or contributed to cloud infrastructure. Use metrics to demonstrate the impact of your work whenever possible.

Prepare for Technical Questions: Anticipate technical questions related to system design, data modelling, and the tech stack mentioned in the job description. Brush up on your knowledge of AWS, Python, and data science concepts to ensure you're ready for the interview process.

How to prepare for a job interview at Climate Policy Radar

✨Understand the Mission

Before your interview, take some time to understand Climate Policy Radar's mission and values. Familiarise yourself with their work in climate policy and AI, as this will help you demonstrate your alignment with their goals during the interview.

✨Showcase Your Technical Skills

Be prepared to discuss your experience with the tech stack mentioned in the job description, particularly Python, data modelling, and MLOps. Bring examples of past projects where you've built scalable data pipelines or worked with machine learning models in production.

✨Prepare for System Design Questions

Since there is a system design interview in the process, brush up on your system architecture knowledge. Be ready to explain your thought process when designing systems, including considerations for scalability, reliability, and cost-effectiveness.

✨Emphasise Collaboration

Highlight your experience working in cross-functional teams. Share specific examples of how you've collaborated with engineers, data scientists, and other stakeholders to achieve project goals, as this aligns with the company's emphasis on teamwork and collaboration.

Data Engineer
Climate Policy Radar
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