At a Glance
- Tasks: Design and maintain data pipelines for real-time AI workloads using cutting-edge technologies.
- Company: Applied Computing, a leader in innovative energy solutions.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Exciting projects with potential for significant impact in the industry.
- Why this job: Join a dynamic team and shape the future of AI in the energy sector.
- Qualifications: Experience in data engineering and familiarity with AWS and Databricks.
The predicted salary is between 63000 - 77000 £ per year.
Applied Computing is seeking a Data Engineer to architect and maintain pipelines turning high-frequency time-series, lab, and historian data into a scalable Lakehouse for deep learning and real-time LLM workloads. You will work across AWS (EKS, S3, EBS, KMS, CloudWatch) and Databricks, ensuring data is contextualised, synchronised, and optimised for AI workloads while solving problems at the intersection of control systems, industrial data engineering, and AI enablement.
Energy AI Data Engineer — Real-Time Lakehouse employer: Applied Computing
Applied Computing is an exceptional employer, offering a dynamic work environment where innovation meets sustainability. As a People Partner, you'll play a crucial role in shaping our People practices while enjoying autonomy and support from a collaborative team. With a focus on employee growth and a commitment to meaningful work, you'll have the opportunity to make a real impact in a fast-paced, scaling organisation dedicated to transforming the energy sector.
StudySmarter Expert Advice🤫
We think this is how you could land Energy AI Data Engineer — Real-Time Lakehouse
✨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 Applied Computing!
✨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 Energy AI Data Engineer — Real-Time Lakehouse at Applied Computing.
✨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 Applied Computing.
✨Apply Directly through Our Website
When you find a suitable opening like Energy AI Data Engineer — Real-Time Lakehouse at Applied Computing, 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 Energy AI Data Engineer — Real-Time Lakehouse
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 Applied Computing, 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 Applied Computing. 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 Applied Computing
✨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 Applied Computing!
✨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.
