Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and optimise automated data pipelines for scalable analytics and business intelligence.
- Company: Join a large enterprise-scale organisation modernising their Data Analytics and Automation Platform.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Why this job: Make a real impact with cutting-edge technology in a dynamic, collaborative environment.
- Qualifications: Experience in data engineering, SQL, and automation tools like Azure Data Factory.
- Other info: Work with international teams and contribute to innovative AI-driven data solutions.
The predicted salary is between 39000 - 46000 £ per year.
Location: Milton Keynes (Hybrid 3 Days In-Office Weekly)
Salary: £45,000 - £55,000
Network IT are supporting a large, enterprise-scale organisation as they continue to evolve and modernise their Data Analytics and Automation Platform; we are looking for an experienced Data Engineer to design, build, and optimise secure, automated data pipelines that enable scalable analytics, business intelligence, and data-driven decision-making across multiple business units.
This is a highly technical role with strong exposure to cloud and on-prem data platforms, automation, and emerging AI-driven capabilities, and is specifically suited to candidates with strong, hands-on data engineering experience, particularly in building, operating, and optimising complex data pipelines, data models, and integration workflows at scale.
Role Overview and Responsibilities
As a Data & Automation Engineer, you will be responsible for the end-to-end delivery, operation, and continuous improvement of enterprise data pipelines and analytics platforms. You will work closely with architects, application managers, and international teams to ensure data solutions are reliable, scalable, and aligned with data governance standards.
Key responsibilities include:
- Designing, developing, and maintaining automated end-to-end data pipelines across cloud and on-premise source systems.
- Delivering reliable data ingestion, transformation, and delivery processes using technologies such as Azure Data Factory, Databricks, SSIS, and SQL.
- Reducing manual interventions through automation and standardisation, including data preparation, feature engineering, and training-data pipelines.
- Preparing data models and datasets (DWH / Lakehouse) to support business intelligence, analytics, and operational reporting.
- Monitoring and supporting live data pipelines, resolving issues in line with ITIL best practices, and implementing proactive alerting and self-healing mechanisms.
- Identifying and implementing performance optimisations across data pipelines, queries, and reporting workloads.
- Supporting data governance processes, including data archiving, masking, encryption, and versioning, with opportunities to integrate AI-driven automation.
- Contributing to CI/CD processes for data pipelines, ensuring releases are tested, compliant, and deployed with minimal operational impact.
- Collaborating with cross-functional and international teams to support aligned, scalable data operations.
- Supporting the ongoing evolution and execution of the organisations data strategy.
Essential Skills and Experience
To be successful in this role, you will bring:
- Strong commercial experience delivering end-to-end data engineering and automation solutions in complex environments.
- Advanced SQL skills, including performance tuning and optimisation across large datasets.
- Knowledge of Python or R for data processing or analytics.
- Hands-on experience with data integration and ingestion tools such as Azure Data Factory and Databricks.
- Proven experience in data modelling, data warehousing, and relational database platforms (e.g. MS SQL Server).
- Experience designing cloud-native and/or on-prem data solutions.
- Exposure to automation and AI-enabled data processes, with awareness of LLM use cases within data workflows.
- Experience working in Agile delivery environments (Scrum, Kanban, DevOps).
- Strong analytical and problem-solving skills, with the ability to translate complex data into meaningful insights.
- Excellent communication skills and the ability to work effectively with both technical and non-technical stakeholders.
Desirable Experience
- Experience coordinating or supporting AI / ML initiatives within data platforms.
- Experience working within large, regulated, or international organisations.
Data Engineer (Automation) in Milton Keynes employer: Network IT
Contact Detail:
Network IT Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (Automation) in Milton Keynes
✨Tip Number 1
Network, network, network! Get out there and connect with people in the industry. Attend meetups, webinars, or even just grab a coffee with someone who works in data engineering. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data pipelines and automation. This is your chance to demonstrate your hands-on experience and make a lasting impression on potential employers.
✨Tip Number 3
Don’t shy away from reaching out directly to companies you’re interested in. A quick email or LinkedIn message can go a long way. Let them know you’re keen on opportunities and how your skills align with their needs.
✨Tip Number 4
Apply through our website! We’ve got loads of resources to help you land that Data Engineer role. Plus, applying directly shows your enthusiasm and commitment to joining the team. Let’s get you started on this exciting journey!
We think you need these skills to ace Data Engineer (Automation) in Milton Keynes
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with data pipelines, automation, and any relevant technologies like Azure Data Factory or Databricks. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background makes you a great fit for our team. Keep it concise but engaging – we love a good story!
Showcase Your Projects: If you've worked on any cool data projects, don’t forget to mention them! Whether it's building automated pipelines or optimising data models, we want to know what you've done and how it relates to the role. Real-world examples can make a big difference.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you'll be able to keep track of your application status. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at Network IT
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Azure Data Factory and Databricks. Brush up on your SQL skills and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges in previous roles. Think about specific instances where you optimised data pipelines or resolved issues, and be ready to explain your thought process.
✨Understand the Business Impact
Be prepared to discuss how your work as a Data Engineer contributes to business intelligence and decision-making. Show that you understand the bigger picture and can translate technical details into business value.
✨Communicate Effectively
Practice explaining technical concepts in simple terms, especially since you'll be working with both technical and non-technical stakeholders. Good communication can set you apart, so think about how you can convey your ideas clearly.
