At a Glance
- Tasks: Build and maintain scalable data pipelines and improve data models for real business impact.
- Company: Dynamic company focused on data-driven solutions with a collaborative culture.
- Benefits: £500 per day contract, hybrid working, and immediate impact on projects.
- Why this job: Make a difference by shaping how data is used across the organisation.
- Qualifications: Strong SQL skills and experience with data warehouse models and production pipelines.
- Other info: Opportunity for hands-on experience in a fast-paced environment.
A Data Engineer is needed for a contract where your work will directly shape how a business trusts, structures, and uses its data. If you enjoy building reliable pipelines, improving models, and turning messy data into dependable assets, this is the kind of project where your impact is felt quickly. This role focuses on practical delivery.
You will be strengthening the foundations of analytics and reporting by building dependable solutions that teams across the organisation rely on every day.
What's in it for you:
- £500 per day contract with immediate impact on a growing environment
- Hybrid working with a balanced onsite and remote setup
- A delivery-focused project where practical engineering skills are valued
- The opportunity to improve and shape core assets used across the business
- A collaborative environment working closely with technical teams and stakeholders
- Real ownership over the reliability and structure of pipelines and models
What you'll be getting stuck into as a Data Engineer:
- Building and maintaining scalable pipelines that support analytics, reporting, and operational data use
- Developing and refining warehouse models that align with real business requirements
- Writing and optimising SQL for transformation, integration, and performance improvements
- Strengthening quality through validation, governance, and structured data workflows
- Delivering reliable, accessible datasets for reporting and decision-making
- Supporting monitoring, testing, and continuous improvement across data processes
What you'll bring to the table as a Data Engineer:
- Strong hands-on experience delivering practical solutions
- Strong SQL capability for transformation, modelling, and optimisation
- Previous experience designing and working with data warehouse models
- Experience building and maintaining production pipelines
- Exposure to platforms such as Databricks, Synapse, or Microsoft Fabric
If you're a Data Engineer ready to step into a contract where you can quickly add value by building dependable pipelines and models, apply now to learn more.
Locations
Data Engineer in Eastleigh, Hampshire employer: TEAM
Contact Detail:
TEAM Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in Eastleigh, Hampshire
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the lookout for opportunities. You never know who might have a lead or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those involving SQL and pipeline building. This will give potential employers a taste of what you can do and how you can add value to their team.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and practical scenarios. Be ready to discuss your experience with platforms like Databricks or Microsoft Fabric, as well as how you've tackled real-world data challenges.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Engineer in Eastleigh, Hampshire
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your hands-on experience with practical solutions, especially in building and maintaining pipelines. We want to see how your skills align with the role, so don’t be shy about showcasing your SQL capabilities and any relevant projects you've worked on.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're excited about this Data Engineer role and how you can make an immediate impact. We love seeing enthusiasm and a clear understanding of what the job entails, so let your personality come through!
Showcase Relevant Experience: When detailing your experience, focus on specific projects where you’ve built scalable pipelines or worked with data warehouse models. We’re looking for concrete examples that demonstrate your ability to deliver reliable solutions and improve data processes.
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 quickly. Plus, it shows us you’re serious about joining our team and making a difference!
How to prepare for a job interview at TEAM
✨Know Your Data Engineering Basics
Make sure you brush up on your data engineering fundamentals. Be ready to discuss your experience with building and maintaining pipelines, as well as your SQL skills. Prepare examples of how you've turned messy data into reliable assets in previous roles.
✨Showcase Your Problem-Solving Skills
During the interview, highlight specific challenges you've faced in past projects and how you overcame them. This is your chance to demonstrate your practical delivery focus and how you can add immediate value to their team.
✨Familiarise Yourself with Relevant Tools
If you have experience with platforms like Databricks, Synapse, or Microsoft Fabric, make sure to mention it. Even if you haven't used them directly, showing that you understand these tools will impress the interviewers and show your readiness to adapt.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's data processes and how they measure success. This not only shows your interest in the role but also gives you a better understanding of how you can contribute to their goals.