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For Companies At a Glance
- Tasks: Build and maintain data pipelines, optimise data architecture, and collaborate with teams.
- Company: Join a fast-growing startup transforming the hospitality industry with a student-powered workforce.
- Benefits: Enjoy a dynamic work environment and the chance to shape innovative solutions.
- Why this job: Be part of a revolutionary platform that enhances efficiency and profitability in hospitality.
- Qualifications: Proficiency in Python and SQL; experience with data frameworks like Airflow or Spark.
- Other info: This role requires 4 days a week onsite; flexibility is essential.
The predicted salary is between 36000 - 60000 £ per year.
My client are a fast-growing startup revolutionising the hospitality industry by connecting businesses with a flexible, student-powered workforce. The platform enables partners—from local pubs to multinational chains—to optimise staffing in real-time, enhancing efficiency and profitability.
As a Data Engineer, you'll play a pivotal role in shaping the data infrastructure. Your responsibilities will include:
- Building and Maintaining Data Pipelines: Design and implement scalable ETL processes to integrate data into our mobile and web applications, as well as internal dashboards.
- Data Architecture Design: Develop and optimise data storage, retrieval, and processing systems to ensure efficiency and scalability.
- Collaboration: Work closely with data scientists, software engineers, and internal stakeholders to understand data needs and deliver solutions that drive data-driven decisions.
- Monitoring and Troubleshooting: Oversee pipeline performance, address issues promptly, and maintain comprehensive data documentation.
What You’ll Bring
- Technical Expertise: Proficiency in Python and SQL; experience with data processing frameworks such as Airflow, Spark, or TensorFlow.
- Data Engineering Fundamentals: Strong understanding of data architecture, data modelling, and scalable data solutions.
- Backend Development: Willingness to develop proficiency in backend technologies (e.g., Python with Django) to support data pipeline integrations.
- Cloud Platforms: Familiarity with AWS or Azure, including services like Apache Airflow, Terraform, or SageMaker.
- Data Quality Management: Experience with data versioning and quality assurance practices.
- Automation and CI/CD: Knowledge of build and deployment automation processes.
Nice to Have
- Production Experience: Experience building and maintaining data pipelines in a live environment.
- Data Storage Solutions: Familiarity with data lakes, warehousing, and other data storage patterns.
- Advanced Tools: Experience with tools like Kafka, Jenkins, Athena, or Spark.
This role will require 4 days per week onsite in the office, this is not optional and you must be open to this in order to proceed with the role.
Contact Detail:
SearchWorks Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarise yourself with the specific data processing frameworks mentioned in the job description, such as Airflow and Spark. Having hands-on experience or projects showcasing your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the hospitality and data engineering sectors. Attend relevant meetups or webinars to connect with people who might provide insights into the company culture and expectations, which can be invaluable during interviews.
✨Tip Number 3
Prepare to discuss your experience with cloud platforms like AWS or Azure. Be ready to share specific examples of how you've used these services in past projects, especially in relation to data storage and processing.
✨Tip Number 4
Showcase your understanding of data quality management and automation processes. Be prepared to explain how you've implemented CI/CD practices in previous roles, as this will demonstrate your ability to maintain high standards in data engineering.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the Data Engineer role. Emphasise your proficiency in Python, SQL, and any data processing frameworks you've worked with.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and how your background fits the company's mission. Mention specific projects or experiences that demonstrate your ability to build and maintain data pipelines.
Showcase Technical Skills: In your application, clearly outline your technical expertise, especially in data architecture and backend development. If you have experience with cloud platforms like AWS or Azure, make sure to highlight that as well.
Prepare for Potential Questions: Anticipate questions related to data quality management and automation processes. Be ready to discuss your experience with CI/CD and any tools you've used, such as Apache Airflow or Spark.
How to prepare for a job interview at SearchWorks
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Python and SQL. Bring examples of past projects where you've implemented ETL processes or worked with data processing frameworks like Airflow or Spark.
✨Understand the Company’s Needs
Research the company and its role in the hospitality industry. Be ready to explain how your skills can help optimise their data infrastructure and support their mission of connecting businesses with a flexible workforce.
✨Demonstrate Collaboration Skills
Since the role involves working closely with data scientists and software engineers, be prepared to share experiences where you successfully collaborated on projects. Highlight your ability to understand and meet the data needs of various stakeholders.
✨Prepare for Practical Scenarios
Expect to face practical questions or scenarios related to monitoring and troubleshooting data pipelines. Brush up on your problem-solving skills and be ready to discuss how you would address common issues in data management.
