At a Glance
- Tasks: Design and maintain data pipelines using Databricks and Apache Spark.
- Company: Join a forward-thinking company offering fully remote work.
- Benefits: Earn £400-500 per day with flexible working arrangements.
- Why this job: Make an impact by optimising data workflows and collaborating with analytics teams.
- Qualifications: 3+ years as a Data Engineer with strong Databricks and Python skills.
- Other info: Exciting opportunity for career growth in a dynamic, remote environment.
The predicted salary is between 80000 - 120000 £ per year.
We are currently recruiting a Data Engineer for one of our clients. The role is outside IR35 and is paying £400-500 per day, it will initially be for 6 months. It is also fully remote.
Key Responsibilities
- Design, develop, and maintain batch and streaming data pipelines using Databricks (Apache Spark)
- Build and optimize ETL/ELT workflows for large-scale structured and unstructured data
- Implement Delta Lake architectures (Bronze/Silver/Gold layers)
- Integrate data from multiple sources (databases, APIs, event streams, files)
- Optimize Spark jobs for performance, scalability, and cost
- Manage data quality, validation, and monitoring
- Collaborate with analytics and ML teams to support reporting and model development
- Implement CI/CD, version control, and automated testing for data pipelines
Required Qualifications
- 3+ years of experience as a Data Engineer
- Strong experience with Databricks and Apache Spark
- Proficiency in Python (required); SQL (advanced)
- Hands-on experience with AWS or Azure cloud services:
- AWS: S3, EMR, Glue, Redshift, Lambda, IAM
- Azure: ADLS Gen2, Azure Databricks, Synapse, Data Factory, Key Vault
Data Engineer in Oxford employer: Searches @ Wenham Carter
Contact Detail:
Searches @ Wenham Carter Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in Oxford
✨Tip Number 1
Network like a pro! Reach out to fellow Data Engineers or industry contacts on LinkedIn. A friendly chat can lead to hidden job opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines, ETL workflows, and any cool projects you've worked on. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for those interviews! Brush up on your Databricks and Apache Spark knowledge, and be ready to discuss how you've tackled data challenges in the past. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented Data Engineers like you. It’s quick and easy, so get your application in today!
We think you need these skills to ace Data Engineer in Oxford
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Databricks, Apache Spark, and any relevant cloud services like AWS or Azure. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include specific projects where you've designed and maintained data pipelines or worked with ETL/ELT workflows. This gives us a clear picture of your hands-on experience and problem-solving skills in action.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for your achievements and responsibilities to make it easy for us to read. We appreciate straightforward communication!
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Searches @ Wenham Carter
✨Know Your Tech Stack
Make sure you brush up on your knowledge of Databricks, Apache Spark, and the cloud services mentioned in the job description. Be ready to discuss how you've used these technologies in past projects, as this will show your practical experience and understanding.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in data engineering and how you overcame them. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easier for the interviewer to follow your thought process.
✨Demonstrate Collaboration
Since the role involves working with analytics and ML teams, be prepared to discuss how you've collaborated with other departments in previous roles. Highlight any successful projects where teamwork was key to achieving results.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the role and the company. Inquire about their current data challenges or how they measure success in their data engineering team. This not only shows your enthusiasm but also helps you gauge if the role is a good fit for you.