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For Companies At a Glance
- Tasks: Design and maintain scalable data systems while collaborating with diverse teams.
- Company: Join a globally renowned, award-winning consultancy making a real impact.
- Benefits: Enjoy hybrid work options, competitive salary, and a dynamic work environment.
- Why this job: Be part of a fast-paced culture that values innovation and teamwork.
- Qualifications: Proficiency in Python, SQL, and cloud-based data solutions required.
- Other info: Work with cutting-edge tools like Azure, Databricks, and more.
The predicted salary is between 60000 - 70000 £ per year.
Data Engineer Opportunity
Location: Hybrid (2 days/week) - Birmingham
Salary: £60,000-£70,000
Are you passionate about creating scalable, reliable data solutions that make a real difference? We’re hiring for a number of Data Engineer roles with a globally renowned, award-winning consultancy.
About the Role
As a Data Engineer, you’ll combine software engineering expertise with cutting-edge data practices to help clients turn data into actionable insights. You’ll design, build, and maintain robust data systems while championing DataOps principles. Working in a fast-paced, agile environment, you’ll collaborate with skilled, multidisciplinary teams to deliver modern data platforms for large organizations. Expect variety – you’ll work across cloud platforms like Azure, AWS, and GCP, leveraging tools such as Databricks, Data Factory, Synapse, Kafka, Glue, Redshift, BigQuery, and more.
About You
You’re an engineer at heart, with a passion for building efficient, scalable data systems. To succeed, you’ll need:
- Proficiency in object-oriented Python and CI/CD pipelines.
- Experience with SQL (complex queries) and ETL processes.
- Strong understanding of cloud-based data storage and processing.
- Knowledge of coding best practices, parallel computing, and workflow automation.
- Expertise in Git/version control and DataOps principles.
- Strong experience with Azure tools, Power BI, or PowerShell.
Key Skills: Databricks, Azure Data Factory, Python, SQL, Medallion Architecture, ETL, Git/version control, Azure Synapse, Power BI.
Data Engineer employer: Xpertise Recruitment
Contact Detail:
Xpertise Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, such as Databricks and Azure Data Factory. Having hands-on experience or projects showcasing your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Network with current Data Engineers or professionals in the field through platforms like LinkedIn. Engaging in conversations about their experiences can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Stay updated on the latest trends in DataOps and cloud technologies. Demonstrating your knowledge of current best practices during interviews can show your commitment to continuous learning and improvement.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges related to Python and SQL. Websites like LeetCode or HackerRank can help you sharpen your skills and boost your confidence before the interview.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, SQL, and cloud platforms like Azure and AWS. Use specific examples of projects where you've implemented DataOps principles or built scalable data systems.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and how your skills align with the job requirements. Mention your familiarity with tools like Databricks and Azure Data Factory, and how you can contribute to the consultancy's goals.
Showcase Relevant Projects: If you have worked on relevant projects, include them in your application. Describe your role, the technologies used, and the impact of your work. This will demonstrate your hands-on experience and problem-solving abilities.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any spelling or grammatical errors. A polished application reflects your attention to detail, which is crucial in data engineering roles.
How to prepare for a job interview at Xpertise Recruitment
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Python, SQL, and any relevant cloud platforms like Azure or AWS. Bring examples of past projects where you implemented ETL processes or built data systems, as this will demonstrate your hands-on experience.
✨Understand DataOps Principles
Familiarise yourself with DataOps principles and be ready to explain how you've applied them in previous roles. This shows that you not only understand the technical aspects but also the importance of collaboration and efficiency in data engineering.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills. Think about challenges you've faced in data engineering and how you overcame them, particularly in fast-paced environments. This will highlight your ability to adapt and innovate.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's data practices, team structure, and the tools they use. This demonstrates your genuine interest in the role and helps you gauge if the company aligns with your career goals.
