At a Glance
- Tasks: Extract and transform data from Azure DevOps using Databricks for impactful metrics dashboards.
- Company: Add Agility, a forward-thinking tech company based in London.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Flexible working environment with a focus on innovation and collaboration.
- Why this job: Join a dynamic team and shape data-driven decisions across multiple tech teams.
- Qualifications: Experience with Databricks, Azure DevOps, and data engineering principles.
The predicted salary is between 51485 - 62926 £ per year.
Add Agility in London is seeking a data engineering specialist to extract data from Azure Dev Ops, transform it in Databricks, and deliver robust datasets powering a metrics dashboard across multiple tech teams.
The role focuses on Databricks pipelines, Azure Dev Ops data, and Palantir Foundry elements, with a hands-on emphasis on building the data layer and metrics.
Hybrid work with two days in London and three days remote.
Hybrid Databricks Data Engineer – Azure DevOps Metrics in London employer: Y-Axis
At Rolls-Royce, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration within our multi-disciplinary teams in Bristol. Our commitment to employee growth is evident through comprehensive training programs and opportunities to lead design activities, ensuring that every team member can thrive while contributing to groundbreaking gas turbine technologies. With generous benefits such as annual leave, group income protection, and a focus on inclusivity, we create an environment where individuals are valued and empowered to make a meaningful impact.
StudySmarter Expert Advice🤫
We think this is how you could land Hybrid Databricks Data Engineer – Azure DevOps Metrics in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Y-Axis!
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We think you need these skills to ace Hybrid Databricks Data Engineer – Azure DevOps Metrics 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 Y-Axis, 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 Y-Axis. 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 Y-Axis
✨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 Y-Axis!
✨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.
