At a Glance
- Tasks: Design and maintain scalable data pipelines using Azure technologies.
- Company: Join a forward-thinking tech company in Manchester with a vibrant culture.
- Benefits: Competitive salary up to £60k, flexible work, and great benefits.
- Other info: Exciting opportunities for growth in a dynamic, collaborative environment.
- Why this job: Make an impact by working on innovative data solutions and cutting-edge technology.
- Qualifications: Experience in data engineering, Azure Data Factory, and strong Python/SQL skills.
The predicted salary is between 60000 - 60000 £ per year.
What you'll be doing:
- Designing and maintaining scalable ELT/ETL pipelines using Azure Data Factory and Microsoft Fabric pipelines
- Implementing medallion architecture (Bronze/Silver/Gold) across the data platform
- Building reliable ingestion from APIs, databases, flat files, and event streams
- Supporting master data management, data quality rules, and golden record definition
- Working hands-on with ADLS, Azure SQL, Event Hubs, Delta Lake, and OneLake
- Designing integration patterns and REST APIs to support near real-time data flows
- Contributing to infrastructure-as-code and environment provisioning in Azure
What you'll bring:
- Solid hands-on data engineering experience - pipelines, ETL/ELT, and data modelling
- Strong Azure Data Factory experience
- Experience with, or strong interest in, Microsoft Fabric (lakehouse and pipeline capabilities)
- Practical understanding of medallion architecture
- Strong Python and/or SQL skills for transformation, automation, and quality checks
- API integration experience and solid grasp of integration design patterns
- Good working knowledge of Azure services: ADLS, Azure SQL, Key Vault, Event Hubs
Nice to have:
- Fabric Lakehouses, Warehouses, and Data Pipelines experience
- Exposure to streaming/event-driven patterns (Event Hubs, Kafka)
- CI/CD and version control experience (Git, Azure DevOps)
- Data governance / Microsoft Purview knowledge
- Background in a high-volume operational or analytical environment
Data Engineer employer: Oliver James Associates Ltd.
Oliver James Associates Ltd. is an excellent employer, offering a dynamic work environment within a long-established London Market Insurance firm that values flexibility and employee well-being. With opportunities for professional growth and development in risk management, employees benefit from a supportive culture that encourages collaboration and innovation, making it an ideal place for those seeking meaningful and rewarding careers in the heart of London.
Contact Details:
Oliver James Associates Ltd. Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
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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 Oliver James Associates Ltd..
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer at Oliver James Associates Ltd., 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
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 Oliver James Associates Ltd., 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 Oliver James Associates Ltd.. 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 Oliver James Associates 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!
✨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 Oliver James Associates 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.
