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- Tasks: Design and build scalable data platforms using Azure and AWS technologies.
- Company: Established tech consultancy with a collaborative engineering culture.
- Benefits: Competitive salary, comprehensive benefits, training, and certification support.
- Why this job: Work on cutting-edge cloud projects and make a real impact in data engineering.
- Qualifications: Experience with large-scale data platforms and strong Python skills.
- Other info: Inclusive environment with opportunities for knowledge sharing and career growth.
The predicted salary is between 36000 - 60000 £ per year.
An established technology consultancy is looking to hire an experienced Data Engineer to work on large-scale, customer-facing data projects while also contributing to the development of internal data services. This role blends hands-on engineering with architecture design and technical advisory work, offering exposure to enterprise clients and modern cloud platforms. You will play a key role in designing and delivering cloud-native data platforms, working closely with engineering teams, stakeholders, and customers from initial design through to production release. The role offers variety, autonomy, and the opportunity to work with leading-edge data technologies across Azure and AWS.
As a Data Engineer, you will be responsible for designing, building, and maintaining scalable data platforms and pipelines. You will support and lead technical workshops, contribute to architecture decisions, and act as a trusted technical partner on complex data initiatives.
Key responsibilities include:
- Designing and building scalable data platforms and ETL/ELT pipelines in Azure and AWS
- Implementing serverless, batch, and streaming data architectures
- Working hands-on with Spark, Python, Databricks, and SQL-based analytics platforms
- Designing Lakehouse-style architectures and analytical data models
- Feeding behavioural and analytical data back into production systems
- Supporting architecture reviews, design sessions, and technical workshops
- Collaborating with engineering, analytics, and commercial teams
- Advising customers throughout the full project lifecycle
- Contributing to internal data services, standards, and best practices
What we are looking for:
Essential experience:
- Proven experience as a Data Engineer working with large-scale data platforms
- Strong hands-on experience in either Azure or AWS, with working knowledge of the other
- Azure experience with Lakehouse concepts, Data Factory, Synapse and/or Fabric
- AWS experience with Redshift, Lambda, and SQL-based analytics services
- Strong Python skills and experience using Apache Spark
- Hands-on experience with Databricks
- Experience designing and maintaining ETL/ELT pipelines
- Solid understanding of data modelling techniques
- Experience working in cross-functional teams on cloud-based data platforms
- Ability to work with SDKs and APIs across cloud services
- Strong communication skills and a customer-focused approach
Desirable experience:
- Data migrations and platform modernisation projects
- Implementing machine learning models using Python
- Consulting or customer-facing engineering roles
Certifications (beneficial but not required):
- AWS Solutions Architect – Associate
- Azure Solutions Architect – Associate
- AWS Data Engineer – Associate
- Azure Data Engineer – Associate
What’s on offer:
- The opportunity to work on modern cloud and data projects using leading technologies
- A collaborative engineering culture with highly skilled colleagues
- Structured learning paths and access to training and certifications
- Certification exam fees covered and certification-related bonuses
- Competitive salary and comprehensive benefits package
- A supportive and inclusive working environment with regular knowledge sharing and team events
This role would suit a Data Engineer who enjoys combining deep technical work with customer interaction and wants to continue developing their expertise across cloud and data platforms.
Data Engineer in Glasgow employer: Nine Twenty
Contact Detail:
Nine Twenty Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in Glasgow
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those who work with data platforms. Attend meetups or webinars related to Azure and AWS to meet potential employers and get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ETL/ELT pipelines or cloud-native architectures. This will give you an edge when chatting with hiring managers about your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and Spark skills. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you think and solve problems!
✨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 and engaged with our company.
We think you need these skills to ace Data Engineer in Glasgow
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences mentioned in the job description. Highlight your hands-on experience with Azure or AWS, and don’t forget to showcase your Python and Spark skills!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you’re the perfect fit for the Data Engineer role. Share specific examples of your past projects and how they relate to the responsibilities listed in the job description.
Showcase Your Technical Skills: When detailing your experience, focus on the technologies and methodologies you’ve used. Mention any relevant projects involving ETL/ELT pipelines, data modelling, or cloud-native architectures to catch our eye!
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 this exciting opportunity!
How to prepare for a job interview at Nine Twenty
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Azure and AWS. Brush up on your skills with Python, Spark, and Databricks, as these will likely come up during technical discussions.
✨Prepare for Scenario-Based Questions
Expect to face scenario-based questions that assess your problem-solving abilities. Think of examples from your past experiences where you designed scalable data platforms or tackled complex data challenges, and be ready to explain your thought process.
✨Showcase Your Communication Skills
Since this role involves collaboration with various teams and stakeholders, demonstrate your strong communication skills. Be prepared to discuss how you’ve effectively communicated technical concepts to non-technical audiences in previous roles.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask insightful questions about the company’s data projects and team dynamics. This shows your genuine interest in the role and helps you gauge if it’s the right fit for you.
