Data Engineer — Databricks & AI Platform (Remote)

Data Engineer — Databricks & AI Platform (Remote)

Full-Time 63000 - 77000 £ / year (est.) Remote
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At a Glance

  • Tasks: Design and optimise data pipelines on Databricks for analytics and reporting.
  • Company: Service Care, a forward-thinking company in the UK.
  • Benefits: Remote work, competitive salary, and opportunities for professional growth.
  • Other info: Collaborate with Data Scientists and Analysts in a supportive environment.
  • Why this job: Join a dynamic team and make an impact with data-driven insights.
  • Qualifications: Experience in data engineering and familiarity with AWS and Databricks.

The predicted salary is between 63000 - 77000 £ per year.

Service Care is seeking an experienced Data Engineer to join its Data, Analytics & Reporting team in the UK.

You’ll design, build and optimise data pipelines on a Databricks platform hosted on AWS, delivering trusted data for analytics, reporting and data science.

You'll work with Data Scientists and Analysts to transform data from clinical, operational and external sources, implement data governance, and contribute to machine learning workflows while maintaining data quality and security.

Data Engineer — Databricks & AI Platform (Remote) employer: Service Care

Service Care Solutions is an excellent employer for Multi Traders, offering a supportive work culture that prioritises employee growth and development. With a focus on responsive repairs in the community of Rugby, employees benefit from a company van, optional on-call payments, and comprehensive in-house training, ensuring they have the tools and skills needed to excel in their roles. Join a team that values professionalism and respect while providing meaningful service to local residents.

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Contact Details:

Service Care Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Engineer — Databricks & AI Platform (Remote)

✨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 Service Care!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer — Databricks & AI Platform (Remote) at Service Care.

✨Leverage Professional Networks

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 Service Care.

✨Apply Directly through Our Website

When you find a suitable opening like Data Engineer — Databricks & AI Platform (Remote) at Service Care, 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 — Databricks & AI Platform (Remote)

Python
Data Governance
Data Engineering
SQL
Problem-Solving Skills
Communication Skills
Data Pipeline Development

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 Service Care, 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 Service Care. 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 Service 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!

✨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 Service Care!

✨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.