At a Glance
- Tasks: Build and maintain scalable data pipelines that power analytics and AI.
- Company: Join a diverse team at a leading tech company focused on innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic environment with a strong focus on collaboration and career advancement.
- Why this job: Make a real impact by ensuring data quality and supporting critical business decisions.
- Qualifications: Proficient in SQL, Python, and have experience with cloud platforms.
The predicted salary is between 45000 - 55000 £ per year.
We are looking for a Data Engineer who takes pride in building data infrastructure that actually works — reliably, at scale, and in production. This is a hands‑on engineering role where you will design and deliver the pipelines, data models, and workflows that power analytics, AI, and business decision‑making across the organisation. If you care about data quality, clean architecture, and engineering that stands up under pressure, this role is for you.
What You'll Be Doing:
- Design, build, and maintain scalable data pipelines and data stores supporting analytics, reporting, and operational use cases.
- Develop and optimise ingestion, transformation, and orchestration workflows across structured and unstructured data sources.
- Embed data quality, lineage, reliability, and security controls throughout the engineering lifecycle.
- Collaborate with analysts, data scientists, and business stakeholders to translate requirements into robust data models and reusable datasets.
- Monitor and troubleshoot data jobs, improve pipeline performance, and support production operations and incident resolution.
- Contribute to technical documentation, coding standards, and deployment and testing automation.
What We're Looking For:
- Strong proficiency in SQL and data modelling — you can design and optimize schemas for performance and scalability.
- Hands‑on experience building ETL/ELT pipelines — from ingestion through transformation to delivery.
- Solid Python skills and practical experience with cloud data platforms (AWS, Azure, or GCP).
- Minimum 2 years of experience in a data engineering or closely related role.
- Bachelor's Degree in Computer Science, Information Systems, Data Science, or a relevant field.
Good to have:
- Experience with Spark or distributed data processing frameworks.
- Familiarity with data warehousing and data lake concepts and architectures.
- Understanding of data governance, security practices, and CI/CD pipelines for data workflows.
Data Engineer in Penarth employer: ACCENTURE SG SERVICES PTE. LTD.
Join a forward-thinking company that values innovation and collaboration, where as a Data Engineer, you will play a crucial role in shaping the data infrastructure that drives impactful business decisions. Our inclusive work culture fosters continuous learning and professional growth, offering you the opportunity to work with cutting-edge technologies in a supportive environment. Located in a vibrant area, we provide a dynamic workplace that encourages creativity and teamwork, making it an excellent place for those seeking meaningful and rewarding employment.
Contact Details:
ACCENTURE SG SERVICES PTE. LTD. Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in Penarth
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We think you need these skills to ace Data Engineer in Penarth
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!
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How to prepare for a job interview at ACCENTURE SG SERVICES PTE. LTD.
✨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!
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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 ACCENTURE SG SERVICES PTE. LTD.!
✨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.
