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For Companies At a Glance
- Tasks: Design and maintain data pipelines using Databricks and Apache Spark.
- Company: Join a forward-thinking company with a focus on data innovation.
- Benefits: Earn £400-500 per day, fully remote work, and flexible hours.
- 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 employer: Searches @ Wenham Carter
Contact Detail:
Searches @ Wenham Carter Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨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 why not give it a go?
We think you need these skills to ace Data Engineer
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.
✨Prepare for Scenario Questions
Expect questions that ask you to solve real-world problems related to data pipelines and ETL workflows. Think about specific challenges you've faced and how you overcame them, especially regarding performance optimisation and data quality management.
✨Showcase Your Collaboration Skills
Since the role involves working with analytics and ML teams, be prepared to talk about your experience collaborating with others. Share examples of how you’ve worked cross-functionally to support reporting or model development, highlighting your communication skills.
✨Demonstrate CI/CD Knowledge
Familiarise yourself with Continuous Integration and Continuous Deployment practices, especially in the context of data engineering. Be ready to explain how you've implemented version control and automated testing in your previous roles, as this is crucial for maintaining robust data pipelines.
