At a Glance
- Tasks: Design and build data pipelines, transforming data for better business decisions.
- Company: Leading tech organisation with a focus on modern data solutions.
- Benefits: Competitive salary, clear career progression, training opportunities, and hybrid work model.
- Other info: Exciting projects with access to emerging technologies like AI and cloud platforms.
- Why this job: Tackle real-world data challenges and make an impact in a collaborative environment.
- Qualifications: Experience in SQL/Python and strong analytical skills required.
The predicted salary is between 40000 - 50000 € per year.
A leading organisation is seeking multiple Data Engineers to join a growing technology team delivering modern data platforms and scalable solutions across a diverse client base.
This role offers the opportunity to work on real-world data challenges, building pipelines, transforming data, and enabling better business decision-making within a collaborative and fast-paced environment.
Responsibilities
- Design and build robust data pipelines and data solutions
- Work with structured and unstructured data from multiple sources
- Develop data models and datasets to support analytics and reporting
- Contribute to the delivery of scalable, cloud-based data platforms
- Collaborate with analysts, engineers, and business stakeholders
- Ensure data quality, accuracy, and performance across solutions
Skills & Experience
- Experience in a Data Engineer, Data Developer, or similar role
- Strong technical skills in SQL and/or Python
- Experience building or working with data pipelines
- Understanding of data modelling and data transformation
- Experience working in Agile or collaborative team environments
- Strong analytical and problem-solving skills
Desirable Experience
- Exposure to AI, machine learning, or advanced analytics
- Experience with cloud platforms such as AWS, Azure, or GCP
- Knowledge of data warehousing or big data technologies
- Interest in emerging technologies such as Generative AI
What's on Offer
- Opportunity to work on large-scale, modern data projects
- Clear career progression and development opportunities
- Access to training, certifications, and new technologies
- Supportive and collaborative working environment
- Hybrid working model based in Belfast
This is an excellent opportunity for Data Engineers looking to develop their skills, work on impactful projects, and progress their careers in a growing and forward-thinking environment.
Apply now for immediate consideration.
Data Engineer - Python/SQL employer: Hays
Join a leading organisation in Belfast as a Data Engineer, where you'll be part of a dynamic technology team dedicated to tackling real-world data challenges. Enjoy a supportive and collaborative work culture that prioritises career growth, offering access to training and certifications while working on large-scale, modern data projects in a hybrid environment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Python/SQL
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, pipelines, and any cool stuff you've built with Python or SQL. This gives you a chance to demonstrate your expertise beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process when solving problems, as this will show your analytical skills and collaborative spirit.
✨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, it shows you're genuinely interested in joining our awesome team.
We think you need these skills to ace Data Engineer - Python/SQL
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with SQL and Python, as well as any work you've done with data pipelines. We want to see how your skills match the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're excited about the Data Engineer role and how your background makes you a great fit. We love seeing passion and personality, so let us know what drives you!
Showcase Your Problem-Solving Skills:In your application, mention specific examples where you've tackled data challenges or improved processes. We’re looking for those strong analytical skills, so don’t hold back on sharing your successes!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s quick and easy, and we can’t wait to see your application come through!
How to prepare for a job interview at Hays
✨Know Your Data Inside Out
Before the interview, brush up on your knowledge of data pipelines, SQL, and Python. Be ready to discuss specific projects where you've designed or built data solutions. This will show your practical experience and understanding of the role.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled data challenges in the past. Think about situations where you had to analyse data quality issues or optimise performance. This will demonstrate your analytical mindset and ability to think critically.
✨Familiarise Yourself with Agile Methodologies
Since the role involves working in a collaborative environment, be prepared to discuss your experience with Agile practices. Highlight any teamwork experiences and how you contributed to project success, as this will resonate well with the interviewers.
✨Stay Updated on Emerging Technologies
Express your interest in AI, machine learning, and cloud platforms like AWS or Azure. Mention any relevant courses or certifications you've pursued. This shows that you're proactive about your professional development and eager to bring new ideas to the team.
