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- Tasks: Design and optimise scalable data pipelines for AI-driven applications.
- Company: Join an innovative AI technology company transforming HealthTech with cutting-edge solutions.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Work on impactful projects in a fast-paced environment with a collaborative team.
- Qualifications: 3+ years in data engineering, strong Python skills, and experience with cloud platforms.
- Other info: Ideal for those passionate about AI innovation and solving complex challenges.
The predicted salary is between 80000 - 110000 £ per year.
Paradigm Talent is currently working with an AI-driven technology company focused on building next-generation automation and intelligence systems for complex, high-stakes environments specifically within the HealthTech space. The team applies advanced machine learning, computer vision, and multimodal AI to solve critical challenges in operational efficiency and decision-making. They work at the cutting edge of deep learning, object recognition, and large-scale AI systems, delivering solutions that drive real-world impact. If you're passionate about research-driven AI innovation and enjoy working on highly technical challenges, this role is for you.
The Role: Data Engineer (Scalable Data & AI Infrastructure)
We’re looking for a Data Engineer with experience in scalable data pipelines, cloud infrastructure, and real-time data processing. You will be responsible for designing, optimising, and maintaining secure, high-performance data architectures that support machine learning, analytics, and automation-driven applications. This role offers the opportunity to work in a fast-paced, data-rich environment, collaborating closely with ML engineers, software developers, and product teams to ensure data reliability, security, and efficiency at scale.
What You’ll Do
- Data Pipeline Development & Optimization: Design, construct, and maintain large-scale data processing and ETL pipelines for structured and unstructured data. Optimize data flow, transformation, and storage, ensuring high efficiency and scalability. Develop and maintain data dashboards for real-time insights and analytics.
- Cloud & Infrastructure Engineering: Work with SQL/NoSQL databases and cloud data services (AWS) to manage and process large datasets. Optimize data warehousing, modeling, and indexing for performance and scalability. Leverage Apache Spark, Airflow, Kafka, or similar technologies to manage and automate workflows.
- Data Security & Quality Control: Ensure data security, compliance, and integrity, implementing best practices for access control and governance. Identify and resolve data quality issues proactively, ensuring clean, accurate, and usable data. Collaborate with machine learning and application engineering teams to prepare data for AI-driven applications.
- Collaboration & Stakeholder Engagement: Work closely with cross-functional teams, including ML researchers, software engineers, and business analysts, to understand data needs and optimize solutions. Support data collection and integration efforts, working with teams across multiple locations to ensure consistency. Bring an analytical mindset, ensuring that data-driven insights align with business and technical goals.
Skills & Experience:
- 3+ years of experience in data engineering or a related field.
- Strong expertise in ETL development, building and maintaining scalable data pipelines.
- Proficiency in Python for data processing and automation.
- Hands-on experience with SQL/NoSQL databases and cloud data platforms (AWS).
- Understanding of data modelling, data warehousing, and database optimisation.
- Experience with distributed data processing tools (Apache Spark, Airflow, Kafka, or similar).
- Proactive approach to identifying and solving data quality issues.
- Strong project management skills, coordinating with cross-functional teams and data capture staff.
Senior Data Engineer employer: Paradigm Talent
Contact Detail:
Paradigm Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Apache Spark, Airflow, and Kafka. Having hands-on experience or projects showcasing your skills with these tools can set you apart during discussions.
✨Tip Number 2
Network with professionals in the HealthTech and AI sectors. Attend relevant meetups or webinars to connect with potential colleagues or hiring managers, which can give you insights into the company culture and expectations.
✨Tip Number 3
Prepare to discuss real-world examples of how you've optimised data pipelines or improved data quality in previous roles. Being able to articulate your problem-solving process will demonstrate your analytical mindset and technical expertise.
✨Tip Number 4
Show your passion for AI-driven innovation by staying updated on the latest trends and advancements in the field. Mentioning recent developments or breakthroughs during your conversations can highlight your enthusiasm and commitment to the industry.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with scalable data pipelines and cloud infrastructure. Use keywords from the job description to demonstrate your fit for the role.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI technology and your experience with machine learning and data processing. Mention specific projects or achievements that align with the responsibilities outlined in the job description.
Showcase Technical Skills: In your application, emphasise your proficiency in Python, SQL/NoSQL databases, and any experience with tools like Apache Spark or Kafka. Providing examples of how you've used these technologies in past roles can strengthen your application.
Highlight Collaboration Experience: Since the role involves working closely with cross-functional teams, include examples of past collaborations with ML engineers or software developers. This will demonstrate your ability to engage with various stakeholders effectively.
How to prepare for a job interview at Paradigm Talent
✨Showcase Your Technical Skills
Be prepared to discuss your experience with ETL development and scalable data pipelines. Highlight specific projects where you've used Python, SQL/NoSQL databases, and cloud platforms like AWS. Demonstrating your hands-on experience with tools like Apache Spark or Kafka will set you apart.
✨Understand the Company’s Focus
Research the AI-driven technology company and its focus on HealthTech. Familiarise yourself with their products and how they apply machine learning and AI. This knowledge will help you tailor your answers and show your genuine interest in their mission.
✨Prepare for Problem-Solving Questions
Expect questions that assess your analytical mindset and problem-solving abilities. Be ready to discuss how you've identified and resolved data quality issues in the past. Use specific examples to illustrate your proactive approach and collaboration with cross-functional teams.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, project management processes, and the technologies they use. This not only shows your interest but also helps you gauge if the company culture aligns with your values and work style.
