At a Glance
- Tasks: Design and maintain scalable data pipelines in a cloud-based environment.
- Company: Join a forward-thinking team in Newcastle with a hybrid work model.
- Benefits: Competitive pay, flexible working, and opportunities for professional growth.
- Other info: Collaborative Agile environment with potential for career advancement.
- Why this job: Make an impact by enhancing data services that drive business decisions.
- Qualifications: Experience in data engineering, SQL, and cloud services required.
The predicted salary is between 63000 - 77000 £ per year.
We are seeking an experienced Data Engineer to support the development and enhancement of large-scale data services within a modern cloud-based environment. This role is ideal for a professional who combines strong data engineering expertise with experience in operational analytics, reporting, and observability platforms. You will be responsible for building and maintaining scalable data pipelines, integrating data from multiple sources, and delivering data products that support business operations and decision-making. Working within Agile delivery teams, you will collaborate with technical and non-technical stakeholders to develop robust, secure, and high-quality data solutions.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and integration solutions.
- Build and optimise ETL/ELT processes for ingesting and transforming data from multiple sources.
- Develop and maintain SQL-based data models and datasets.
- Create and enhance reporting and dashboard solutions using Qlik technologies.
- Utilise Kibana and Elasticsearch for operational analytics, monitoring, and data exploration.
- Integrate data from APIs, databases, and third-party services.
- Ensure data quality, consistency, governance, and documentation standards are met.
- Support and enhance cloud-native data services within AWS environments.
- Implement and maintain CI/CD deployment pipelines and version control processes.
- Work closely with stakeholders to gather requirements and translate business needs into technical solutions.
- Contribute to Agile ceremonies, sprint planning, estimation, and continuous improvement initiatives.
Essential Skills & Experience
- Strong commercial experience as a Data Engineer, Analytics Engineer, ETL Developer, or similar role.
- Proven expertise in SQL and data modelling.
- Experience designing and supporting ETL/ELT and data integration solutions.
- Strong hands-on experience with: Qlik Sense and/or QlikView, Kibana, Elasticsearch / ELK Stack.
- Experience building and maintaining data pipelines.
- Knowledge of dashboarding and data visualisation best practices.
- Experience working with AWS cloud services and cloud-native architectures.
- API-based data ingestion and integration experience.
- Experience with Git and CI/CD deployment practices.
- Strong understanding of Agile delivery methodologies.
- Excellent stakeholder management and communication skills.
Desirable Experience
- Government, Public Sector, or highly regulated industry experience.
- Experience supporting live digital services or operational platforms.
- Knowledge of data governance and data quality frameworks.
- Exposure to observability, monitoring, or service analytics environments.
- Previous experience working within secure or SC-cleared programmes.
Data Engineer in Newcastle upon Tyne employer: Opus Recruitment Solutions
Join a forward-thinking company that values innovation and collaboration, offering a dynamic work culture where your contributions as a ServiceNow Mapping Product Lead will directly impact large-scale digital transformation initiatives. With a focus on employee growth, we provide ample opportunities for professional development and the chance to work alongside industry leaders in a hybrid environment that promotes work-life balance. Our commitment to excellence and support for your career aspirations make us an exceptional employer in the tech landscape.
Contact Details:
Opus Recruitment Solutions Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in Newcastle upon Tyne
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Opus Recruitment Solutions!
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Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer at Opus Recruitment Solutions.
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Opus Recruitment Solutions.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer at Opus Recruitment Solutions, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Engineer in Newcastle upon Tyne
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Opus Recruitment Solutions, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Opus Recruitment Solutions. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Opus Recruitment Solutions
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Opus Recruitment Solutions!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
