At a Glance
- Tasks: Build and optimise data pipelines while driving AI and Machine Learning initiatives.
- Company: Join a dynamic team at a leading media company focused on data-driven insights.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Other info: Diverse and inclusive workplace with a focus on continuous learning.
- Why this job: Make an impact by leveraging cutting-edge technology in a fast-paced environment.
- Qualifications: Experience in Python, SQL, and cloud platforms; strong analytical skills required.
The predicted salary is between 50000 - 70000 £ per year.
Reports to: Director of Data Science & Engineering
We are looking for a Data Engineer with Machine Learning experience to join our team. They will be responsible for maintaining and supporting the existing data infrastructure used to underpin our data analytics and reporting. The Data Engineer will own the company's drive into Machine Learning and AI adoption. They will be accountable for building as well as owning new Machine Learning and AI solutions across the team and the wider business. These must complement our current, scalable data architecture.
The Data Engineer will support the customer analytics function by developing and deploying machine learning models and techniques to deliver value around our consumer (B2C) data. They will be expected to optimize the architecture of our data pipelines and ensure that data flows support various cross-functional teams across the business. The ideal candidate will have a self-directed, innovative mindset who is comfortable supporting the data needs of multiple teams. The right candidate will be proactive in identifying and implementing improvements for our systems contributing constructively to the current data ecosystem.
As the business continues to invest in cloud solutions, particularly Google Cloud Platform, you will be excited by the prospect of owning new projects, propelling our data initiatives and capabilities. Lead Data Engineer will be exposed to best practice methods with the current framework.
The Data & Marketing Department is the intelligence powerhouse of the business, representing the customer. Our goal is to inspire, engage and grow a loyal readership by harnessing data-driven insights and innovative marketing to deliver personalised, impactful content experiences that build lasting trust, diverse revenue streams, and a thriving future for quality journalism.
An accomplished ML/Data Engineer with proven experience deploying and managing ML and AI based services in production. Strong SQL skills and hands-on experience with both relational and non-relational databases, supporting data needs in fast-paced, content-driven environments. Strong expertise in designing and maintaining scalable data pipelines and architectures—integrating data from web analytics, content management systems (CMS), subscription platforms, ad tech, and social media.
Proven ability to automate and optimise data workflows, using modern ETL/ELT tools (e.g., Airflow, dbt, Apache Spark) to ensure timely and reliable delivery of data. Experience building robust data models and reporting layers to support performance dashboards, user engagement analytics, ad revenue tracking, and A/B testing frameworks. Skilled in cloud-based data platforms and infrastructure (e.g., AWS, GCP), ensuring scalability and security for large volumes of streaming and batch data. Additionally, experience with data warehouses such as BigQuery or Snowflake.
Adept in Python and/or Java for developing data services and integrating APIs to bring in diverse sources of media data. Exposure to utilising AI and Agentic workflows to build and deploy models agents and coding pipelines. Ideally having experience in Gemini, Claude and Vertex AI. Exposure to ML Frameworks such as PyTorch or TensorFlow. Understanding of ML Ops such as automated model testing, monitoring and tuning.
Excellent interpersonal and communication skills, enabling effective collaboration with analytical and commercial teams to turn data into actionable insights. Proactive and self-driven, capable of managing multiple data projects in a high tempo setting while meeting tight deadlines. A continuous learner with a diligent approach to data engineering including data privacy.
Diversity, Equity and Inclusion: We champion diversity in our teams and in our reporting. As a growing and global brand, we must have a workforce that’s more representative of our readers, viewers, clients and partners, and a workplace that creates a sense of belonging for everyone.
Design and Maintain Data Pipelines: Develop and maintain robust, scalable, and efficient data pipeline architecture to support current and future business needs. Identify, design, and implement improvements to automate manual processes, enhance data delivery performance, and re-architect infrastructure for improved scalability and resilience.
AI Agentic Workflows: Build on the current usage of AI across the business rolling out new processes and models.
Machine Learning: Take the lead in building out our capability in this area with new models and recommender systems.
ETL Development and Infrastructure Building: Build and manage the infrastructure necessary for optimal ETL or ELT of data using Python, SQL, and Google Cloud Platform (GCP) big data technologies, such as BigQuery, Dataflow, Dataproc and Cloud Storage.
Business Intelligence Enablement: Prepare and transform pipeline data to support downstream analytics and feed BI tools (DOMO), enabling data-driven decision-making across the organization. Partner with internal stakeholders—ranging from Data, Commercial, and Editorial teams to executive leadership—to address data-related technical challenges and support their infrastructure needs.
Enhance Data System Functionality: Collaborate with the Data Team to continuously improve the functionality, flexibility, and performance of data systems and platforms.
Data Governance and Compliance: Ensure all data is handled responsibly, securely, and in full compliance with the Data Protection Act, GDPR regulations, and the Company’s Code of Conduct.
SQL and Database Expertise: Strong working knowledge of SQL with hands-on experience querying and managing relational databases, alongside familiarity with a variety of database technologies (e.g., PostgreSQL, MySQL, BigQuery).
Big Data Engineering: Proven experience designing, building, and optimizing ‘big data’ pipelines, architectures, and datasets, enabling efficient data processing at scale. Skilled in performing root cause analysis on complex internal and external data sources and business processes to resolve issues and uncover opportunities for operational or strategic improvements.
Unstructured Data Handling: Strong analytical capability for working with unstructured and semi-structured datasets, transforming raw information into actionable insights.
Data Workflow Development: Expertise in developing and maintaining data transformation processes, managing data structures, metadata, workload dependencies, and orchestration frameworks.
Large-scale Data Processing: Excellent project management and organizational skills, with experience supporting and collaborating with cross-functional teams in dynamic and evolving settings. Holds a graduate degree in Computer Science, STEM related quantitative field, with 2+ years of hands-on experience in a data engineering role.
Databases: Proficient in SQL databases.
Programming Languages: Skilled in one or more of the following languages, i.e.: Python, Java, Go.
Inclusive: We champion diversity in our teams and in our reporting. We take risks and are always looking to try new ideas in pursuit of excellence.
Data Engineer (Remote, Python) in London employer: The Independent
Join a forward-thinking company that values innovation and diversity, where as a Data Engineer, you will play a pivotal role in shaping our machine learning and AI initiatives. Enjoy a collaborative work culture that encourages continuous learning and offers ample opportunities for professional growth, all while working remotely from the comfort of your own home. With a commitment to data-driven insights and a focus on building a representative workforce, this is an excellent opportunity for those looking to make a meaningful impact in the world of data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (Remote, Python) in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those involving Machine Learning and AI. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the company’s data architecture. Be ready to discuss how you can optimise their data pipelines and contribute to their AI initiatives.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Engineer (Remote, Python) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Python, SQL, and any machine learning projects you've worked on. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for data engineering and AI, and explain why you’re excited about joining StudySmarter. Let us know how you can contribute to our data initiatives.
Showcase Your Projects:If you've got any relevant projects or contributions to open-source, don’t hold back! Include links or descriptions in your application. We love seeing practical examples of your work and how you tackle challenges.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows you’re keen on being part of our team at StudySmarter!
How to prepare for a job interview at The Independent
✨Know Your Data Engineering Basics
Make sure you brush up on your data engineering fundamentals, especially around SQL and Python. Be ready to discuss your experience with building and optimising data pipelines, as well as any hands-on projects you've worked on that involved big data technologies like GCP or AWS.
✨Showcase Your Machine Learning Experience
Since the role involves machine learning, be prepared to talk about specific models you've built or deployed. Highlight your familiarity with ML frameworks like PyTorch or TensorFlow, and share examples of how you've integrated AI into data workflows.
✨Demonstrate Problem-Solving Skills
Expect questions that assess your ability to troubleshoot and optimise data systems. Think of scenarios where you've identified bottlenecks in data processing and how you resolved them. This will show your proactive mindset and innovative approach.
✨Communicate Effectively
As collaboration is key in this role, practice articulating complex technical concepts in a way that's easy for non-technical stakeholders to understand. Prepare to discuss how you've worked with cross-functional teams to turn data insights into actionable strategies.
