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- Tasks: Design and develop data infrastructure for Data Science projects while maintaining existing systems.
- Company: Join a leading independent sports betting company known for innovation and excellence.
- Benefits: Enjoy remote work options, competitive salary, and opportunities for professional growth.
- Why this job: Work with cutting-edge tech, collaborate with talented teams, and make a real impact in the industry.
- Qualifications: Master’s degree in Computer Science or equivalent experience; strong Python and SQL skills required.
- Other info: No prior experience necessary; a passion for learning and development is key.
The predicted salary is between 44000 - 60000 £ per year.
A leading independent sports betting company is looking to hire a Data Engineer with a strong background in Python and SQL to support its talented data science team.
You will be exposed to and supported in your development of maintaining existing infrastructure such as AirFlow instances and Kubernetes clusters, that are used by the data science team to provide critical services to the business. Prior experience is not necessary.
As a Data Engineer, you will be responsible for designing and developing robust data infrastructure required to deliver Data Science projects. In addition to this, you will be maintaining the existing infrastructure, such as Airflow instances and Kubernetes clusters, that are used by Data Science to provide critical services to the business. You will work closely with the Analytics team to identify opportunities for growth and optimization, using data to inform our strategies and drive success.
In this role, you will also have the opportunity to support the Data Science function within the team, sharing your expertise and collaborating with other members to make their data-driven approach even stronger. You will also have the chance to work with cutting-edge technologies and tools.
Responsibilities
- Designing and developing data infrastructure requirements to deliver data science functions and working closely with the DevOps team in provisioning Kubernetes clusters.
- Working on large data sets across the business and collaborating with senior stakeholders.
Minimum Requirements
- A Master’s degree in Computer Science or equivalent experience in a quantitative field (e.g. Statistics, Mathematics, Machine Learning, Engineering).
- Proven experience as a Data Engineer, particularly with Python and SQL.
- Experience in Airflow, Terraform, Git, GitLab (including CI/CD pipelines) and GCP (particularly Kubernetes and Helm) is a plus – you must want to learn and develop your current experience with these.
Apply for this job
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Data Engineer £55,000 - £75,000 plus benefits London, United Kingdom (remote) employer: Chisquare Group
Contact Detail:
Chisquare Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer £55,000 - £75,000 plus benefits London, United Kingdom (remote)
✨Tip Number 1
Familiarize yourself with the specific technologies mentioned in the job description, such as Airflow and Kubernetes. Even if you don't have prior experience, showing a willingness to learn these tools can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the data engineering field, especially those who work with sports betting or similar industries. Engaging with them on platforms like LinkedIn can provide insights and potentially lead to referrals.
✨Tip Number 3
Highlight any projects or experiences where you've worked with large datasets or collaborated with cross-functional teams. This will demonstrate your ability to handle the responsibilities outlined in the job description.
✨Tip Number 4
Prepare for potential technical interviews by practicing coding challenges in Python and SQL. Being able to showcase your problem-solving skills in these languages will be crucial in landing the job.
We think you need these skills to ace Data Engineer £55,000 - £75,000 plus benefits London, United Kingdom (remote)
Some tips for your application 🫡
Highlight Relevant Skills: Make sure to emphasize your experience with Python and SQL in your application. Mention any projects or roles where you utilized these skills, as they are crucial for the Data Engineer position.
Showcase Your Education: Since a Master’s degree in Computer Science or a related quantitative field is required, clearly state your educational background. Include any relevant coursework or projects that align with data engineering.
Demonstrate Willingness to Learn: The company values candidates who are eager to learn and develop their skills. In your cover letter, express your enthusiasm for working with technologies like Airflow, Kubernetes, and GCP, even if you have limited experience with them.
Tailor Your Application: Customize your CV and cover letter to reflect the specific responsibilities and requirements mentioned in the job description. Use keywords from the listing to ensure your application stands out to hiring managers.
How to prepare for a job interview at Chisquare Group
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and SQL in detail. Highlight specific projects where you've utilized these skills, and be ready to solve a coding challenge or answer technical questions related to data engineering.
✨Familiarize Yourself with Relevant Tools
Since the role involves working with Airflow, Kubernetes, and GCP, make sure you understand how these tools work. Even if you haven't used them extensively, showing a willingness to learn and discussing any relevant experience will impress the interviewers.
✨Demonstrate Collaboration Skills
This position requires working closely with the Analytics team and other stakeholders. Prepare examples of how you've successfully collaborated in past roles, emphasizing your communication skills and ability to work in a team environment.
✨Prepare Questions About Growth Opportunities
Express your interest in professional development by asking about opportunities for learning and growth within the company. This shows that you're not only focused on the job at hand but also on your long-term career trajectory.
