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- Tasks: Help clients unlock data potential by building and maintaining high-performance data pipelines.
- Company: Join a forward-thinking UK-based data consultancy leading the industry in data strategy and analytics.
- Benefits: Enjoy a dynamic work environment with opportunities for professional growth and collaboration.
- Why this job: Be part of a team that values innovation and makes a real impact in the data landscape.
- Qualifications: Expertise in Databricks, SQL, and Apache Spark required; familiarity with modern data technologies is a plus.
- Other info: Ideal for self-motivated team players passionate about data and AI; UK work rights needed.
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 specifically requires expertise in Databricks, consider exploring online tutorials or courses that focus on building data solutions using this platform. This will not only boost your confidence but also demonstrate your commitment to mastering the tools essential for the job.
✨Tip Number 2
Network with professionals in the data engineering field, especially those who work with Databricks or similar technologies. Attend industry meetups, webinars, or online forums where you can connect with others and gain insights into the latest trends and best practices. This could lead to valuable referrals or recommendations.
✨Tip Number 3
Prepare to discuss real-world scenarios where you've successfully implemented data solutions. Think of specific examples that highlight your skills in SQL, Apache Spark, and data pipeline architecture. Being able to articulate your experience clearly will set you apart during interviews.
✨Tip Number 4
Stay updated on the latest developments in data engineering and related technologies. Follow relevant blogs, podcasts, or social media channels to keep your knowledge fresh. Showing that you're proactive about learning can impress potential employers and demonstrate your passion for the field.
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 requires strong collaboration with clients and teams, emphasise your communication and teamwork skills. Provide examples of how you've effectively engaged with stakeholders in past projects.
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 successfully built and deployed data solutions, as this will demonstrate your hands-on expertise.
✨Understand the Data Engineering Lifecycle
Familiarise yourself with the entire data engineering lifecycle, including Agile delivery and DevOps practices. Be ready to explain how you have applied these methodologies in past roles to improve efficiency and collaboration.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills. Think of examples where you've identified challenges in data pipelines and how you proposed scalable solutions to overcome them.
✨Engage with Stakeholders
Since the role involves working closely with clients and cross-functional teams, prepare to discuss how you've effectively communicated technical concepts to non-technical stakeholders in previous positions.
