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For Companies At a Glance
- Tasks: Design and implement scalable data pipelines for cutting-edge AI initiatives.
- Company: Join a team dedicated to solving humanity's toughest challenges through advanced technology.
- Benefits: Enjoy a hybrid work model with flexibility between Oxford and London, plus a collaborative culture.
- Why this job: Make a lasting impact while working with world-leading scientists and innovators in a creative environment.
- Qualifications: Experience in data engineering, cloud technologies, and strong programming skills are essential.
- Other info: This role is perfect for those passionate about AI and data-driven solutions.
The predicted salary is between 43200 - 72000 £ per year.
Data Engineers (All Levels)
About the Organization
Our client is dedicated to developing and deploying advanced technology to solve some of humanity's most challenging and enduring problems. Guided by world-leading scientists and entrepreneurs, they accelerate innovation by driving scientific and technological advancements across critical areas such as health and medical science, food security, sustainable agriculture, climate change, clean energy, and the era of artificial intelligence. Their collaborative culture fosters curiosity, creativity, and a deep sense of responsibility, empowering their team to achieve excellence and make a lasting impact.
The Role
Our client is seeking a Data Engineers at all Levels who will drive the deployment of a data platform to underpin the development of cutting-edge AI initiatives. The Data Engineers will be responsible for critical components of the data infrastructure and pipeline development, playing a key role in architecting scalable data systems that power AI models and products.
This position requires technical expertise in scaling data processing systems for high-performance AI applications, along with the ability to collaborate effectively with diverse teams, including scientists, innovators, operations professionals, and researchers from various fields.
Key Responsibilities
- Design and implement components of robust, scalable data pipelines and infrastructure.
- Lead the development of data processing systems using cloud technologies.
- Optimize data storage and retrieval for high-performance AI applications.
- Collaborate with AI/ML teams to support model development and deployment.
- Evaluate and integrate new technologies to enhance data capabilities.
- Partner and collaborate with diverse teams, including science, research, product, business development, and operations.
Ideal Candidate
- Significant experience in data engineering at scale.
- Strong knowledge of data management tools and technologies, including ETL frameworks, database engines, and file/object stores.
- Experience building secure and scalable platforms/products on cloud infrastructure.
- Proven experience partnering with research and product teams.
- Strong software engineering background with software design and architecture skills.
- Extensive enterprise programming experience writing production code in mainstream programming languages (e.g., Python).
- Experience with data modeling, ETL processes, and data warehousing.
- Familiarity with ML/AI workflows and data requirements.
Location
This role is Hybrid, Candidates are expected to be onsite in Oxford at least 1 day a week and the other days Hybrid London/Home.
Data Engineer employer: Hlx Life Sciences
Contact Detail:
Hlx Life Sciences Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarize yourself with the latest cloud technologies and data management tools. Since the role emphasizes building secure and scalable platforms on cloud infrastructure, having hands-on experience with these technologies will set you apart.
✨Tip Number 2
Showcase your collaboration skills by highlighting any past experiences where you worked with diverse teams. This role requires effective communication with scientists, researchers, and product teams, so demonstrating your ability to work in a team-oriented environment is crucial.
✨Tip Number 3
Stay updated on the latest trends in AI and machine learning workflows. Understanding the data requirements for these technologies will help you align your skills with the needs of the role and demonstrate your commitment to continuous learning.
✨Tip Number 4
Prepare to discuss specific projects where you've implemented scalable data pipelines or optimized data storage solutions. Being able to provide concrete examples of your work will illustrate your technical expertise and problem-solving abilities.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description and understand the key responsibilities and ideal candidate profile. Tailor your application to highlight your relevant experience in data engineering, cloud technologies, and collaboration with diverse teams.
Highlight Technical Skills: Emphasize your technical expertise in data management tools, ETL frameworks, and programming languages like Python. Provide specific examples of projects where you designed scalable data pipelines or optimized data storage for AI applications.
Showcase Collaboration Experience: Since the role involves working with various teams, include examples of how you've successfully collaborated with scientists, researchers, or product teams in previous roles. This will demonstrate your ability to work effectively in a multidisciplinary environment.
Craft a Strong Cover Letter: Write a compelling cover letter that connects your background and skills to the mission of the organization. Express your enthusiasm for contributing to innovative solutions in areas like health, climate change, and AI, and explain why you're a great fit for their team.
How to prepare for a job interview at Hlx Life Sciences
✨Showcase Your Technical Skills
Be prepared to discuss your experience with data management tools and technologies. Highlight specific projects where you designed and implemented scalable data pipelines, and be ready to explain the technical challenges you faced and how you overcame them.
✨Demonstrate Collaboration Experience
Since the role involves working with diverse teams, share examples of how you've successfully collaborated with scientists, researchers, or product teams in the past. Emphasize your ability to communicate complex technical concepts to non-technical stakeholders.
✨Familiarize Yourself with AI/ML Workflows
Understand the basics of machine learning and artificial intelligence workflows. Be ready to discuss how your data engineering skills can support model development and deployment, and mention any relevant experience you have in this area.
✨Prepare Questions About the Company’s Vision
Research the organization’s mission and recent projects related to health, climate change, or clean energy. Prepare thoughtful questions that show your interest in their work and how you can contribute to their goals as a Data Engineer.
