At a Glance
- Tasks: Build scalable data platforms and design innovative data solutions using Databricks.
- Company: DataArt, a leading tech company in London with a focus on collaboration.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Exciting projects with excellent career advancement opportunities.
- Why this job: Join a dynamic team and work on cutting-edge Azure technologies to make an impact.
- Qualifications: Strong experience with Databricks and knowledge of ETL/ELT workflows.
The predicted salary is between 63000 - 77000 £ per year.
Data Art in London is seeking a Strong Middle / Senior Databricks Developer to build scalable data platforms on Microsoft Azure.
You will design data solutions with Databricks, develop end-to-end pipelines, and implement Lakehouse architectures using Delta Lake.
You will collaborate with Data Engineers, Data Architects, Analytics teams and business stakeholders to optimise ETL/ELT workflows, ensure data quality, governance and security, and support CI/CD and infrastructure automation.
Senior Databricks Engineer - Azure Lakehouse & Spark in London employer: DataArt
DataArt is an exceptional employer that fosters a collaborative and innovative work culture, particularly for those passionate about AI in the Healthcare & Life Sciences sector. With a strong emphasis on employee growth, you will have access to cutting-edge projects and the opportunity to lead transformative solutions that make a real difference in people's lives. Located in a vibrant tech hub, DataArt offers unique advantages such as flexible working arrangements and a commitment to professional development, making it an ideal place for talented individuals seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Databricks Engineer - Azure Lakehouse & Spark in London
✨Get Involved in Data Science Meetups
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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 DataArt.
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We think you need these skills to ace Senior Databricks Engineer - Azure Lakehouse & Spark 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!
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 DataArt, 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 DataArt. 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 DataArt
✨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 DataArt!
✨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.
