At a Glance
- Tasks: Design and implement end-to-end features for scalable analytics and performance.
- Company: Join Oracle, a leader in innovative technology solutions.
- Benefits: Enjoy competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on innovation and career advancement.
- Why this job: Make an impact by optimising data systems and enhancing performance in a dynamic environment.
- Qualifications: Experience in software development, data modelling, and secure coding practices.
The predicted salary is between 67500 - 82500 £ per year.
Oracle is seeking a Software Developer to design and implement end-to-end features across application and data layers in a role with growing autonomy.
You will craft data models (star/snowflake) for analytics, optimize queries, and debug performance issues while leveraging Oracle APEX and PL/SQL.
Secure coding and thorough documentation of service contracts are essential.
In this position you will apply telemetry to monitor usage, latency and conversions, and you will participate in code reviews
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Senior Data Systems Engineer: Scalable Analytics & Performance employer: Oracle
Oracle is an exceptional employer, offering a dynamic work culture that prioritises innovation and collaboration in the heart of Greater London. Employees benefit from comprehensive professional development opportunities, competitive compensation, and a commitment to operational excellence within cutting-edge data centre environments. Join us to be part of a forward-thinking team that values your expertise and fosters growth in a vibrant city.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Systems Engineer: Scalable Analytics & Performance
✨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 Oracle!
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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 Oracle.
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We think you need these skills to ace Senior Data Systems Engineer: Scalable Analytics & Performance
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 Oracle, 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 Oracle. 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 Oracle
✨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 Oracle!
✨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.
