At a Glance
- Tasks: Design and implement ETL/ELT pipelines on Azure for data solutions.
- Company: Voyage Care, a leader in specialist care services.
- Benefits: Salary between £30,000 to £55,000, 25 days leave, and pension.
- Other info: Hybrid work model with opportunities for collaboration and growth.
- Why this job: Join a dynamic team and enhance data quality and governance.
- Qualifications: Experience in data engineering and Azure technologies.
Voyage Care is seeking an experienced Data Engineer to join our hybrid Data & Analytics team in Lichfield, working one day per week at the Group Support Office. You will design end-to-end ETL/ELT pipelines on Azure to deliver production-grade data solutions for our specialist care services.
The role focuses on data quality, governance, security, and collaboration with internal teams and partners. Salary ranges from £30,000 to £55,000 per year with 25 days leave and a pension.
#J-18808-LjbffrHybrid Azure Data Engineer – ETL, Synapse & Governance in Shenstone employer: Voyage-Care
Voyage Care is an exceptional employer that prioritises the well-being and growth of its employees. Located in the welcoming community of Bo'ness, we offer competitive pay, comprehensive training, and ample opportunities for career advancement within a dynamic team dedicated to making a meaningful impact in the lives of those we support.
StudySmarter Expert Advice🤫
We think this is how you could land Hybrid Azure Data Engineer – ETL, Synapse & Governance in Shenstone
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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 Voyage-Care
✨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!
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✨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.