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- Tasks: Help clients unlock data potential through engineering and analytics.
- Company: Join a forward-thinking UK-based data consultancy leading in data strategy.
- Benefits: Enjoy flexible work options and a collaborative team culture.
- Other info: Must have the right to work in the UK; no visa sponsorship available.
- Why this job: Be at the forefront of data innovation and make a real impact.
- Qualifications: Expertise in Databricks, SQL, and Apache Spark required; certifications are a plus.
The predicted salary is between 36000 - 60000 £ per year.
Data Engineer – Data Consultancy
A forward-thinking UK-based data consultancy is seeking talented Data Engineers to help clients unlock the full potential of their data assets. In this role, you’ll be instrumental in guiding organisations through the evolving landscape of data strategy, engineering, and analytics
Key Responsibilities:
- Forge strong partnerships with clients and cross-functional teams, bridging the gap between business needs and technical solutions.
- Deliver high-impact work with precision, proactively identifying challenges and proposing smart, scalable solutions.
- Architect and maintain resilient, high-performance data pipelines (ETL/ELT) to ingest, transform, and deliver data from diverse sources.
Required Skills & Experience:
- Deep expertise in building and deploying data solutions using platforms like Databricks (Azure/AWS) , Microsoft Fabric , Azure Data Factory , and Azure Synapse .
- Strong skills in SQL and Apache Spark (Scala or Python).
- A strong foundation in data disciplines such as governance , architecture , modelling , data lakes , warehousing , MDM , and BI .
- Advanced skills in SQL and Python , with hands-on experience in relational databases across cloud and on-prem environments.
- Familiarity with modern data technologies such as Apache Spark , Kafka , or Snowflake .
- A comprehensive understanding of the data engineering lifecycle, including Agile delivery , DevOps , Git , APIs , containers , microservices , and pipeline orchestration .
Nice to have:
- Databricks Certified Data Engineer Associate
- Databricks Certified Data Engineer Professional
The ideal candidate will be a self-motivated team player with a proven track record of delivering accurate, insightful solutions under pressure, able to work independently or collaboratively to meet tight deadlines and engage confidently with senior stakeholders.
If you are passionate about data and AI and are ready to take a leadership role in a forward-thinking, UK based consultancy at the forefront of the industry, we would love to hear from you.
Please note: Applicants must have the right to work in the UK. Visa sponsorship is not available, either now or in the future.
Data Engineer - Databricks employer: Alvarium Talent
Contact Detail:
Alvarium Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - Databricks
✨Tip Number 1
Familiarise yourself with Databricks and its ecosystem. Since this role heavily relies on Databricks, showcasing your hands-on experience with it during discussions can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the data engineering field, especially those who work with Azure and Databricks. Engaging in conversations about current trends and challenges can provide insights that may be beneficial during interviews.
✨Tip Number 3
Prepare to discuss specific projects where you've implemented ETL/ELT processes. Being able to articulate your problem-solving approach and the impact of your solutions will demonstrate your capability to deliver high-impact work.
✨Tip Number 4
Brush up on your SQL and Apache Spark skills, particularly in Python or Scala. Practical demonstrations of your coding abilities during technical interviews can significantly enhance your chances of landing the job.
We think you need these skills to ace Data Engineer - Databricks
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Databricks, SQL, and Apache Spark. Use specific examples of projects where you've built data pipelines or worked with cloud technologies to demonstrate your expertise.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data and AI. Mention how your skills align with the company's needs and provide examples of how you've successfully delivered data solutions in previous roles.
Showcase Relevant Projects: If you have any personal or professional projects that showcase your skills in data engineering, especially using Databricks or similar platforms, include them in your application. This can set you apart from other candidates.
Highlight Soft Skills: Since the role involves working with clients and cross-functional teams, emphasise your communication and teamwork skills. Provide examples of how you've effectively collaborated with others to achieve project goals.
How to prepare for a job interview at Alvarium Talent
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Databricks, SQL, and Apache Spark in detail. Highlight specific projects where you've built or deployed data solutions, and be ready to explain the challenges you faced and how you overcame them.
✨Understand the Data Engineering Lifecycle
Familiarise yourself with the entire data engineering lifecycle, including Agile delivery and DevOps practices. Be ready to discuss how you've applied these methodologies in past roles, as this will demonstrate your comprehensive understanding of the field.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills. Think about how you would approach common challenges in data engineering, such as optimising data pipelines or ensuring data governance, and articulate your thought process clearly.
✨Engage with Stakeholders
Since the role involves working closely with clients and cross-functional teams, practice articulating complex technical concepts in a way that non-technical stakeholders can understand. This will show your ability to bridge the gap between business needs and technical solutions.