At a Glance
- Tasks: Design and build scalable data pipelines using Databricks to transform data into insights.
- Company: Join a forward-thinking tech company with a collaborative and inclusive culture.
- Benefits: Enjoy competitive pay, flexible working, and access to accredited training courses.
- Other info: Hybrid work model with opportunities for career growth and continuous improvement.
- Why this job: Make a real impact on data engineering projects while developing your skills in a dynamic environment.
- Qualifications: Experience with Databricks, Python, and data engineering principles is essential.
The predicted salary is between 60000 - 80000 £ per year.
We are expanding our Data Engineering capability to support a growing client data platform built on modern cloud architecture. We are seeking a Databricks Data Engineer to accelerate the ingestion, processing, and transformation of data into a scalable analytics platform, delivering tangible business value at pace. This role will work closely with client stakeholders and internal teams to design, build, and optimise robust data pipelines while contributing to the evolution of an enterprise-grade data platform leveraging industry best practices.
Responsibilities
- Design, build, and maintain scalable data pipelines using Databricks (Azure Databricks preferred)
- Develop and manage efficient data ingestion frameworks for onboarding diverse data sources
- Implement and optimise Delta Lake and Medallion (Bronze/Silver/Gold) architecture
- Collaborate with business, analytics, and reporting teams to structure data for optimal consumption
- Support the expansion and enhancement of the data platform, focusing on performance, scalability, and reliability
- Integrate and process data from multiple sources, including tools such as Qlik Replicate or similar CDC technologies
- Apply data modelling best practices to ensure high-quality, reusable datasets
- Monitor, troubleshoot, and optimise pipelines to ensure availability and performance
- Contribute to CI/CD, automation, and DevOps practices within data engineering workflows
- Work collaboratively within Agile delivery teams (Scrum / Kanban)
Essential skills
- Good understanding of data engineering principles
- Medallion Lakehouse architecture
- Python / PySpark and SQL
- Data analysis, reporting, and consumption layers (e.g. Power BI)
- Solid understanding of data modelling principles
Desired skills
- Familiarity with Qlik Replicate or similar data integration / CDC tools
- Knowledge of data governance and data quality frameworks
- Exposure to streaming data processing (e.g., Spark Structured Streaming)
Soft Skills
- Strong stakeholder engagement and communication skills
- Ability to work effectively in collaborative, distributed teams
- Proactive, delivery-focused mindset with a commitment to quality
- Adaptable and able to ramp up quickly in new environments
- Passion for continuous improvement and data engineering excellence
Experience
- Strong hands-on experience with Databricks, Spark, PySpark, and Delta Lake
- Proven experience building and maintaining ETL/ELT pipelines
- Experience working with modern cloud data platforms (Azure, AWS, or GCP)
- Experience working in Agile delivery environments
- Experience within Commercial Insurance / London Market / Financial Services
- Experience supporting analytics and reporting use cases
What do I need before I apply
Hybrid / Remote with travel to London 1–2 days per week as required
Benefits
- Collaborative working environment – we stand shoulder to shoulder with our clients and our peers through good times and challenges
- We empower all passionate technology loving professionals by allowing them to expand their skills and take part in inspiring projects
- Expleo Academy - enables you to acquire and develop the right skills by delivering a suite of accredited training courses
- Competitive company benefits
- Always working as one team, our people are not afraid to think big and challenge the status quo
As a Disability Confident Committed Employer we have committed to: Ensure our recruitment process is inclusive and accessible, communicating and promoting vacancies, offering an interview to disabled people who meet the minimum criteria for the job, anticipating and providing reasonable adjustments as required, supporting any existing employee who acquires a disability or long term health condition, enabling them to stay in work.
We are an equal opportunities employer and welcome applications from all suitably qualified persons regardless of their race, sex, disability, religion/belief, sexual orientation or age. We treat everyone fairly and equitably across the organisation, including providing any additional support and adjustments needed for everyone to thrive.
Databricks Data Engineer in London employer: Expleo
At Expleo, we pride ourselves on fostering a collaborative and inclusive work environment where technology enthusiasts can thrive. As a Databricks Data Engineer, you'll have the opportunity to work on cutting-edge projects while benefiting from our commitment to continuous learning through the Expleo Academy. With a focus on employee growth and a supportive culture, we empower our team members to challenge the status quo and make a meaningful impact in the data engineering landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Databricks Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Databricks. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Databricks, Spark, and Delta Lake. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with data pipelines and how you've tackled challenges in previous roles. We want to see your passion for data engineering!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive and eager to join our team.
We think you need these skills to ace Databricks Data Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the Databricks Data Engineer role. Highlight your experience with data pipelines, Databricks, and any relevant cloud platforms. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're passionate about data engineering and how you can contribute to our team. Be sure to mention any specific projects or experiences that relate to the job description.
Showcase Your Technical Skills:Don’t hold back on showcasing your technical prowess! Include specific examples of your work with Python, PySpark, and Delta Lake. We love seeing how you've tackled challenges in previous roles, so share those stories!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Plus, it’s super easy!
How to prepare for a job interview at Expleo
✨Know Your Databricks Inside Out
Make sure you brush up on your Databricks skills, especially if Azure Databricks is preferred. Be ready to discuss how you've designed and built scalable data pipelines in the past, and have examples at hand that showcase your experience with Delta Lake and Medallion architecture.
✨Showcase Your Collaboration Skills
This role involves working closely with various teams, so be prepared to talk about your experience in collaborative environments. Share specific instances where you've engaged with stakeholders or worked within Agile teams, highlighting your communication skills and ability to adapt.
✨Demonstrate Your Problem-Solving Mindset
Employers love candidates who can troubleshoot and optimise data pipelines. Think of challenges you've faced in previous roles and how you overcame them. This will show your proactive approach and commitment to quality, which are key for this position.
✨Prepare for Technical Questions
Expect technical questions related to data engineering principles, Python, PySpark, and SQL. Brush up on your data modelling best practices and be ready to discuss how you've applied them in real-world scenarios. This will help you stand out as a knowledgeable candidate.
