At a Glance
- Tasks: Build and optimise data pipelines while driving AI and Machine Learning initiatives.
- Company: Join a dynamic team at a leading data-driven organisation.
- Benefits: Fully remote work, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on diversity and inclusion.
- Why this job: Be at the forefront of AI and data innovation, making a real impact.
- Qualifications: Experience in data engineering, SQL, and cloud platforms like GCP.
The predicted salary is between 55000 - 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: AI adoption: 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: Project Management & Collaboration: 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.
Fully Remote Data Engineer employer: The Independent
Join a forward-thinking company that champions innovation and diversity, offering a fully remote Data Engineer role where you can lead the charge in Machine Learning and AI adoption. With a strong focus on employee growth, you'll have access to continuous learning opportunities and the chance to collaborate with cross-functional teams, all while enjoying a flexible work culture that values your contributions and promotes a sense of belonging.
StudySmarter Expert Advice🤫
We think this is how you could land Fully Remote Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend virtual 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 engineering projects, especially those involving machine learning and cloud platforms. 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 latest trends in data engineering and AI. Practice common interview questions and be ready to discuss how you've tackled challenges in past projects.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your relevant experience and enthusiasm for the role.
We think you need these skills to ace Fully Remote Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with machine learning, data pipelines, and cloud platforms like GCP. 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 how you can contribute to our team. Don’t forget to mention any innovative projects you've worked on that relate to AI and ML.
Showcase Your Technical Skills:Be specific about your technical expertise in SQL, Python, and big data technologies. We love seeing hands-on experience, so include examples of how you've built or optimised data architectures in the past.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen to join our team!
How to prepare for a job interview at The Independent
✨Know Your Data Inside Out
Before the interview, make sure you’re well-versed in the data technologies mentioned in the job description. Brush up on your SQL skills and be ready to discuss your experience with databases like BigQuery or Snowflake. Being able to talk confidently about your past projects will show that you’re not just familiar with the tools, but you’ve actually used them effectively.
✨Showcase Your Machine Learning Experience
Since this role involves a strong focus on Machine Learning, prepare to discuss specific ML models you've built or deployed. Be ready to explain the challenges you faced and how you overcame them. If you have experience with frameworks like PyTorch or TensorFlow, highlight that too—it’ll set you apart from other candidates.
✨Demonstrate Your Problem-Solving Skills
Expect questions that assess your ability to troubleshoot and optimise data workflows. Think of examples where you identified inefficiencies in data pipelines and how you improved them. This will show your proactive mindset and your capability to contribute constructively to the data ecosystem.
✨Be Ready for Technical Questions
Prepare for technical questions that may involve coding or designing data architectures on the spot. Practise common data engineering problems and be familiar with ETL/ELT processes. This will not only demonstrate your technical prowess but also your ability to think critically under pressure.
