At a Glance
- Tasks: Lead the transformation of a core data platform with real-time data pipelines.
- Company: Retelligence, a forward-thinking tech company in London.
- Benefits: Flexible working, competitive pay, and opportunities for professional growth.
- Other info: Enjoy autonomy and a dynamic work culture focused on innovation.
- Why this job: Make a significant impact on data architecture in a multi-cloud environment.
- Qualifications: Experience in Python, SQL, Spark, dbt, and Terraform is essential.
The predicted salary is between 63000 - 77000 £ per year.
Retelligence in London is seeking a Senior Data Engineer for a high-impact modernization of a core data platform.
This Outside IR35 engagement offers autonomy to evaluate current architecture and implement robust, real-time data pipelines across multi-cloud environments.
You will own the delivery of multi-cloud data flows using Python, SQL, Spark, dbt, and Terraform, with CI/CD and data governance as core priorities.
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Senior Data Engineer - Multi-Cloud Data Platform & ETL in London employer: Retelligence
At Retelligence, we pride ourselves on fostering a dynamic work culture that encourages innovation and collaboration. As a Senior AI Infrastructure Engineer, you'll not only tackle complex challenges but also have access to continuous learning opportunities and career growth, all while making a tangible impact on our customers. Located in a vibrant tech hub, we offer a supportive environment where your contributions are valued and recognised.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer - Multi-Cloud Data Platform & ETL in London
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We think you need these skills to ace Senior Data Engineer - Multi-Cloud Data Platform & ETL in London
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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Craft a Tailored Cover Letter:For a full-time role at Retelligence, 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 Retelligence. 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 Retelligence
✨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 Retelligence!
✨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.
