At a Glance
- Tasks: Develop scalable data systems and efficient workflows using cutting-edge AI tools.
- Company: Leading AI analytics firm backed by a multinational equity company.
- Benefits: Competitive salary, remote work, and opportunities for professional growth.
- Other info: Limited interview slots available; apply now to secure your chance!
- Why this job: Join a rapidly growing team and work with the latest technology in AI.
- Qualifications: Experience with Spark, Scala, Java, and cloud data systems.
The predicted salary is between 60000 - 80000 £ per year.
My client is based in the London area, is currently looking to recruit an experienced Data Engineer to join their AI Analytics team. They are one of the leaders within the AI space and are currently going through a period of growth.
Main Responsibilities:
- Develop scalable systems and reusable components that serve as reference points for new team members.
- Create efficient data workflows using distributed computing tools, particularly for large-scale processing and aggregation.
- Build responsive, asynchronous APIs and backend processes capable of handling high data volumes with minimal delay.
- Utilise AI-powered development tools to enhance productivity and code quality.
- Collaborate within Agile teams to refine and monitor data collection systems using Scala and Java.
- Apply sound engineering principles such as test-driven development and modular design.
Preferred Background:
- Hands-on experience with Spark and Scala in commercial environments.
- Familiarity with Java and Python.
- Exposure to distributed data systems and cloud storage platforms.
- Experience designing data schemas and analytical databases.
- Use of AI tools to streamline development and debugging.
- Strong grasp of algorithmic thinking and performance optimisation.
- Proficiency with SQL and NoSQL databases such as PostgreSQL and Cassandra.
- Experience with systems like Kafka or RabbitMQ.
- Ability to build and manage ETL pipelines using tools like Airflow.
This role is an urgent requirement. There are limited interview slots left. If interested, send an up-to-date CV to Shoaib Khan.
Remote Senior Data Engineer in Halifax employer: Tenth Revolution Group
Join a forward-thinking company at the forefront of AI technology, where your expertise as a Senior Data Engineer will be valued and nurtured. With a strong emphasis on employee growth, collaborative Agile teams, and access to cutting-edge tools, you'll thrive in a dynamic work culture that prioritises innovation and excellence. Located in London, this role offers the unique advantage of being part of a rapidly growing organisation backed by a multinational equity firm, ensuring a stable and exciting career path.
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We think this is how you could land Remote Senior Data Engineer in Halifax
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We think you need these skills to ace Remote Senior Data Engineer in Halifax
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!
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How to prepare for a job interview at Tenth Revolution Group
✨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!
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✨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 Tenth Revolution Group!
✨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.
