At a Glance
- Tasks: Design and build scalable data solutions for analytics and AI.
- Company: Join a leading tech firm in Newcastle with a focus on innovation.
- Benefits: Hybrid working, competitive salary, and opportunities for rapid career growth.
- Other info: Collaborative environment with opportunities to mentor junior engineers.
- Why this job: Make an impact by shaping large-scale data solutions with cutting-edge technologies.
- Qualifications: 3+ years in data engineering, strong Java or Python skills, and cloud experience.
The predicted salary is between 50000 - 60000 £ per year.
Location: Newcastle Upon Tyne
Salary: TBC – Depending on experience
Levels: Senior Analyst, Specialist
Hybrid Working: 3 days per week in our Newcastle, Cobalt business park office
Please Note: Any offer of employment is subject to satisfactory BPSS and SC security clearance which requires 5 years continuous UK address history (typically including no periods of 30 consecutive days or more spent outside of the UK) and declaration of being a British or EU passport holder or hold Indefinite Leave to remain within the UK at the point of application.
About the Team
Our Advanced Technology Centre is a hub of innovation where we deliver high‑quality data and technology services to clients across both the public and private sectors. If you're looking for a dynamic role that offers hands‑on experience with modern data technologies and the chance to shape large‑scale data solutions, this position offers you the opportunity to develop and progress rapidly.
Role Overview
As a Data Engineer, you will design, build, and maintain scalable data solutions that enable analytics, AI, and operational insights. You’ll work alongside client and internal teams to create robust data pipelines, ensure data reliability, and support cloud‑based architectures that power intelligent decision‑making.
Key Responsibilities
- Data Pipeline Development: Build, optimize, and maintain scalable data pipelines using Java (primary), plus exposure to Python, Flink, Kafka, or Spark. Develop and support real‑time streaming pipelines and event‑driven integrations. Integrate data from multiple sources (streaming, batch, APIs) using AWS managed services (e.g., Kinesis, MSK, Lambda, Glue).
- Data Architecture & Standards: Contribute to data modelling, data architecture best practices, and modern patterns (e.g., medallion architecture). Ensure data quality, lineage, governance, and security controls are applied consistently.
- DevOps & Deployment: Deploy and maintain data applications using CI/CD tooling (Azure DevOps, GitHub Actions, Jenkins). Use Infrastructure as Code (Terraform, CloudFormation) to manage cloud environments. Work with container technologies such as Docker and Kubernetes‑based workloads.
- Collaboration: Work closely with analytics, ML/AI, and product teams to deliver clean, well‑structured datasets. Participate in code reviews and internal knowledge‑sharing sessions. Provide guidance to junior engineers where needed.
Qualification
- Core Data Engineering: Strong programming proficiency in Java (preferred) or Python. Hands‑on experience with at least one of: Kafka, Flink, Spark (Flink/Kafka preferred for streaming). Solid understanding of stream processing concepts (e.g., event time, state, backpressure). Understanding of software engineering best practices: testing, design patterns, CI/CD, Git. Experience building ETL/ELT or streaming data pipelines. Exposure to microservices and distributed system concepts. Experience working with cloud platforms, ideally AWS, but Azure/GCP also acceptable. Understanding of distributed compute, large‑scale data systems, and performance considerations.
- DevOps & Engineering Practices: Experience with CI/CD tools (Azure DevOps, GitHub Actions, Jenkins etc.). Infrastructure‑as‑Code (Terraform preferred). Experience with containerisation (Docker) and orchestration platforms (Kubernetes/EKS).
- Certifications & Tools: Exposure to enterprise data platforms (Databricks, Snowflake, BigQuery, or similar). Cloud certifications (AWS, Azure, GCP) are beneficial but not required.
Other Requirements
- Minimum 3 years’ experience working on data engineering or large‑scale data solutions.
- Comfortable working in Agile delivery teams.
- Strong communication skills and ability to collaborate with technical and non‑technical stakeholders.
Desirable
- Experience in client‑facing or consulting environments.
- Professional cloud or data engineering certifications.
- Experience mentoring or supporting junior engineers.
- Background in designing or operating real‑time, low‑latency systems.
Data Engineer: Real-Time Pipelines & Cloud Data (Hybrid) in Newcastle upon Tyne employer: 慨正橡扯
Join our Advanced Technology Centre in Newcastle Upon Tyne, where innovation meets collaboration. As a Data Engineer, you'll thrive in a dynamic work culture that values hands-on experience with cutting-edge data technologies and offers ample opportunities for professional growth. Enjoy the flexibility of hybrid working while contributing to impactful projects that shape the future of data solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer: Real-Time Pipelines & Cloud Data (Hybrid) in Newcastle upon Tyne
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and common data engineering questions. Practice explaining your past projects and how you tackled challenges – confidence is key!
✨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: Real-Time Pipelines & Cloud Data (Hybrid) in Newcastle upon Tyne
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Java, data pipelines, and cloud technologies. 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! Share your passion for data engineering and how you can contribute to our Advanced Technology Centre. Let us know why you're excited about this opportunity!
Showcase Relevant Projects:If you've worked on any relevant projects, make sure to mention them! Whether it's building scalable data solutions or using AWS services, we love to see practical examples of your work.
Apply Through Our Website:Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can't wait to hear from you!
How to prepare for a job interview at 慨正橡扯
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Java, Kafka, and AWS services. Brush up on your knowledge of data pipelines and streaming concepts, as these will likely come up during technical questions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built or optimised data pipelines. Be ready to explain your role, the challenges you faced, and how you overcame them. This will demonstrate your hands-on experience and problem-solving skills.
✨Understand the Company’s Needs
Research the company and its clients to understand their data challenges. Tailor your answers to show how your skills can help solve these issues. This shows that you’re not just looking for any job, but that you’re genuinely interested in contributing to their success.
✨Practice Collaboration Scenarios
Since collaboration is key in this role, think of examples where you’ve worked with cross-functional teams. Be prepared to discuss how you communicated complex technical concepts to non-technical stakeholders, as this will highlight your communication skills.
