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- Tasks: Design and maintain backend systems and data pipelines for AI solutions.
- Company: Fortune 500 tech leader transforming businesses with innovative digital solutions.
- Benefits: Competitive salary, health benefits, remote work options, and career development opportunities.
- Other info: Exciting projects with potential for significant career growth in a global company.
- Why this job: Join a dynamic team and shape the future of AI in a collaborative environment.
- Qualifications: Experience in backend and data engineering, with strong database management skills.
The predicted salary is between 50000 - 70000 £ per year.
Insight Enterprises, Inc. is a Fortune 500 solutions integrator helping organizations accelerate their digital journey to modernize their business and maximize the value of technology. Insight’s technical expertise spans cloud and edge-based transformation solutions, with global scale and optimization built on 33+ years of deep partnerships with the world’s leading and emerging technology providers.
We are seeking a highly skilled and motivated Backend + Data Engineer to join our AI Coach development team. In this role, you will be designing, building, and maintaining our backend infrastructure and data pipelines that power our core applications and data analytics capabilities. You will collaborate closely with cross-functional teams including frontend, AI engineering and product managers, and frontend developers to deliver scalable, reliable, and efficient solutions. This position requires a strong foundation in backend systems, proficiency in database management, and expertise in data engineering to handle large datasets and ensure data quality and availability. You will have the opportunity to work on new Insight initiatives to bring AI solutions to the wider Insight sales community.
Responsibilities
- Design, develop, and maintain backend services and APIs to support business applications.
- Build and optimize scalable data pipelines and ETL processes to ingest, process, and transform large volumes of data.
- Ensure data quality, integrity, and consistency across multiple data sources and databases.
- Collaborate with data scientists and analysts to enable efficient data access and analysis.
- Implement monitoring, alerting, and performance tuning for backend systems and data workflows.
- Participate in architectural discussions and contribute to technology roadmap decisions.
- Troubleshoot and resolve backend and data-related issues promptly to minimize downtime.
- Develop and maintain documentation for backend systems and data engineering processes.
Requirements
- Proven experience as a backend engineer and data engineer or in a combined role.
- Strong understanding of relational and NoSQL databases, including experience with query optimization.
- Hands‑on experience with data pipeline and workflow management tools like Apache Airflow or similar.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and associated data services.
- Knowledge of containerization and orchestration technologies such as Docker and Kubernetes.
- Excellent problem‑solving skills and ability to work independently and in a team environment.
- Strong communication skills to collaborate effectively across multiple teams.
Data Engineer employer: Insight
Contact Detail:
Insight Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Data Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving backend systems and data pipelines. We want to see what you can do, so make it easy for potential employers to check out your work.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to data engineering and backend development. We recommend practicing coding challenges and discussing your thought process out loud to impress your interviewers.
✨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
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your backend and data engineering experience, and don’t forget to mention any relevant projects or technologies you’ve worked with that match the job description.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about the role and how your skills align with Insight’s mission. Keep it concise but impactful, and let your personality show through.
Showcase Your Technical Skills: Be specific about your technical skills in your application. Mention your experience with databases, data pipelines, and any cloud platforms you’ve used. This will help us see how you can contribute to our AI Coach development team.
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’s super easy!
How to prepare for a job interview at Insight
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like relational and NoSQL databases, Apache Airflow, and cloud platforms. Brush up on your knowledge of Docker and Kubernetes too, as these are crucial for the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you tackled them. Insight Enterprises values excellent problem-solving skills, so have a few examples ready that highlight your ability to think critically and work independently.
✨Collaboration is Key
Since this role involves working closely with cross-functional teams, be ready to talk about your experience collaborating with data scientists, analysts, and frontend developers. Highlight any successful projects where teamwork played a vital role in achieving results.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s AI initiatives and how they plan to leverage data engineering in their projects. This shows your genuine interest in the role and helps you understand how you can contribute to their goals.