At a Glance
- Tasks: Build and optimise cloud-based data platforms and scalable data pipelines.
- Company: Leading organisation in digital transformation with a collaborative culture.
- Benefits: Competitive day rate, hybrid working, ongoing training, and clear career progression.
- Other info: Exciting opportunities for growth and innovation in a fast-paced environment.
- Why this job: Join a dynamic team and work with cutting-edge cloud technologies.
- Qualifications: Up to 2 years' experience in Data Engineering or related fields, strong SQL skills.
The predicted salary is between 63000 - 77000 £ per year.
A leading organisation undergoing a major digital transformation is looking to expand its Data & Integration team with the addition of a Data Engineer. This is an exciting opportunity to join a growing data function responsible for building modern cloud-based data platforms that support reporting, business intelligence, analytics, and future AI capabilities. You'll work alongside experienced Data Engineers, Solution Architects, and Product Owners while developing your skills with the latest cloud and data technologies.
We are hiring a Data Engineer to support the development, maintenance, and optimisation of enterprise data platforms and integration solutions. Working within a collaborative engineering team, you'll help build scalable data pipelines, improve data quality, and contribute to the delivery of cloud-based data solutions that enable better business decision-making.
Key Responsibilities:- Develop and maintain data pipelines to ingest, transform, and load data from multiple sources
- Build and support scalable ETL/ELT processes and data integration solutions
- Assist with the design and maintenance of enterprise data platforms
- Develop data models and datasets to support reporting and analytics
- Monitor pipeline performance and resolve data quality issues
- Work closely with Data Analysts, Software Engineers, and business stakeholders to understand data requirements
- Support testing, deployment, and ongoing maintenance of data solutions
- Contribute to DataOps, DevOps, and CI/CD best practices
- Assist with data governance, security, and compliance initiatives
- Identify opportunities to automate processes and improve platform performance
We're looking for an enthusiastic Data Engineer with a passion for cloud technologies and modern data platforms.
Essential Experience:- Up to 2 years' experience in Data Engineering, Software Engineering, Analytics, or a similar technical role
- Strong SQL skills and understanding of relational databases
- Experience with Python or other data-focused programming languages
- Understanding of ETL/ELT processes and data integration concepts
- Knowledge of data modelling and database design principles
- Familiarity with Git or other version control systems
- Strong analytical and problem-solving skills
- Excellent communication and stakeholder engagement skills
- Keen interest in cloud technologies and modern data engineering practices
- Ability to work collaboratively within Agile delivery teams
- Microsoft Azure (AZ-900) or DP-900 certifications
- Experience with Microsoft Fabric, Azure Data Factory, Databricks, or similar cloud data platforms
- Exposure to Power BI and reporting solutions
- Experience working with APIs and data ingestion technologies
- Knowledge of CI/CD, DataOps, Docker, or Kubernetes
- Understanding of data warehousing concepts
- Previous internship, placement year, graduate programme, or commercial experience in a data-focused role
- Competitive salary
- Hybrid and flexible working
- Opportunity to work with modern Microsoft cloud technologies
- Hands-on experience with Microsoft Fabric, Azure Data Factory, Databricks, and enterprise data platforms
- Ongoing training, mentoring, and certification support
- Clear career progression into Senior and Principal Data Engineering roles
- Collaborative engineering culture focused on innovation and continuous improvement
- Multi-stage interview process
- Technical and competency-based assessments
- Fast-moving recruitment process
Data Engineer – Hybrid – Day Rate in Reading employer: Pearson Carter
At Pearson Carter, we pride ourselves on being an excellent employer by fostering a collaborative and supportive work culture that values employee growth and development. Our Skegness location offers unique advantages, including a close-knit community and the opportunity to work directly with clients, ensuring that your contributions have a meaningful impact. Join us to be part of a team that is dedicated to maximizing ERP investments while providing you with the resources and training needed to excel in your career.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer – Hybrid – Day Rate in Reading
✨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 Pearson Carter!
✨Show Off Your Projects
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 – Hybrid – Day Rate at Pearson Carter.
✨Leverage Professional Networks
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 Pearson Carter.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer – Hybrid – Day Rate at Pearson Carter, 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 – Hybrid – Day Rate in Reading
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 Pearson Carter, 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 Pearson Carter. 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 Pearson Carter
✨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 Pearson Carter!
✨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.
