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- Tasks: Join a dynamic team to manage ETL, build data pipelines, and enhance data infrastructure.
- Company: Be part of a leading data-rich organisation with over 3 million customers in the UK.
- Benefits: Enjoy flexible work with just two days in the office each month and great corporate perks.
- Why this job: Work on exciting real-time projects and collaborate with experienced data professionals in a supportive culture.
- Qualifications: Strong degree in computer science and excellent Python coding skills required; experience with Spark and AWS preferred.
- Other info: Opportunity to work with cutting-edge tools and technologies in a well-regarded Data division.
The predicted salary is between 54000 - 84000 £ per year.
Xcede are delighted to be working with an incredibly data-rich organisation with over 3 million customers in the UK using their products. The company has a very established Data division headed up by a well-regarded CDO who comes from a ‘hands-on’ Data Science background. The Data Unit is filled with experienced Data Scientists, Analysts, Machine Learning Engineers, LLM specialists, and Data Engineers.
We’re now actively recruiting for another Senior Data Engineer to join their team. The perfect Senior Data Engineer will love building great Software as much as they do exploring & managing data. The company adheres to Software Engineering best practices and will expect any new joiners to do the same.
Alongside the huge swathe of batch data that they work with, the team also has a clear business opportunity to work on real-time / streaming projects.
- Manage ETL, build pipelines, and scale data infrastructure to support data science and analytics initiatives.
- Design, implement and improve tools and services for orchestration, observability, data governance and data quality to high engineering standards.
- Work in partnership with Analytical stakeholders from a huge variety of business projects and help to diagnose issues.
Ideally, a strong degree in computer science or a relevant area is required. Excellent coding skills specifically in Python are essential. Very desirable commercial technical experience with tools such as Spark, Databricks, Airflow, Docker etc. Commercial Containerisation & Infrastructure as code experience is also preferred. AWS is the preferred cloud platform - Azure and/or GCP will be considered.
Sr. Data Science Engineer employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Sr. Data Science Engineer
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, such as Spark, Databricks, and Airflow. Having hands-on experience or projects showcasing your skills with these technologies can set you apart from other candidates.
✨Tip Number 2
Network with current or former employees of the company to gain insights into their data division and culture. This can help you tailor your approach and demonstrate your genuine interest in joining their team.
✨Tip Number 3
Prepare to discuss your experience with ETL processes and data pipeline management in detail. Be ready to share specific examples of how you've improved data quality and governance in previous roles.
✨Tip Number 4
Showcase your coding skills in Python by working on relevant projects or contributing to open-source initiatives. Highlighting your ability to write clean, efficient code will resonate well with the company's emphasis on software engineering best practices.
We think you need these skills to ace Sr. Data Science Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with tools like Python, Spark, and AWS. Emphasise any projects where you've built data pipelines or managed ETL processes.
Craft a Strong Cover Letter: In your cover letter, express your passion for data and software engineering. Mention specific projects or experiences that align with the company's focus on real-time data and analytics initiatives.
Showcase Technical Skills: Clearly list your technical skills, especially those mentioned in the job description such as Docker, Airflow, and cloud platforms. Provide examples of how you've used these tools in past roles.
Highlight Collaboration Experience: Since the role involves working with analytical stakeholders, include examples of how you've successfully collaborated with cross-functional teams to solve data-related issues or improve processes.
How to prepare for a job interview at Xcede
✨Showcase Your Technical Skills
Be prepared to discuss your coding skills, especially in Python. Bring examples of your previous work with tools like Spark, Databricks, and Airflow. Demonstrating your hands-on experience will impress the interviewers.
✨Understand the Business Context
Familiarise yourself with the company's data-rich environment and their customer base. Understanding how your role as a Senior Data Engineer can impact business projects will show your commitment and strategic thinking.
✨Discuss Best Practices
Since the company adheres to Software Engineering best practices, be ready to talk about your experience with ETL processes, data governance, and quality assurance. Highlight how you ensure high engineering standards in your work.
✨Prepare for Real-Time Data Challenges
Given the focus on real-time and streaming projects, think of examples where you've tackled similar challenges. Discuss your approach to building scalable data infrastructure and how you manage data pipelines effectively.
