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For Companies At a Glance
- Tasks: Own and optimise the centralised data platform using SQL and Power BI.
- Company: Join a well-established organisation in Newark with a strong reputation.
- Benefits: Enjoy a competitive salary and a collaborative work environment.
- Why this job: Be part of a dynamic team and make a real impact on data management.
- Qualifications: Confident in SQL, data warehousing, and Power BI; experience preferred.
- Other info: Opportunity to step into a role as a current team member transitions out.
The predicted salary is between 35000 - 38000 £ per year.
A well-established organisation in the Newark area is seeking a Data Warehouse Engineer to take ownership of its centralised data platform. With a current team member transitioning out at the end of July, this role is ideal for someone confident in SQL, data warehousing, and Power BI, who can hit the ground running in a collaborative environment.
Salary: £35,000-£38,000
Data Warehouse engineer employer: SF Recruitment (Tech)
Contact Detail:
SF Recruitment (Tech) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Warehouse engineer
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as SQL, data warehousing concepts, and Power BI. Having hands-on experience or projects showcasing these skills can set you apart from other candidates.
✨Tip Number 2
Network with current or former employees of the organisation to gain insights into their work culture and expectations. This can help you tailor your approach during interviews and demonstrate your genuine interest in the role.
✨Tip Number 3
Prepare for technical interviews by practising common data warehousing scenarios and SQL queries. Being able to solve problems on the spot will show your confidence and capability in handling the responsibilities of the role.
✨Tip Number 4
Showcase your collaborative skills during the interview process. Since the role involves working within a team, providing examples of past teamwork experiences can highlight your ability to contribute positively to the team dynamic.
We think you need these skills to ace Data Warehouse engineer
Some tips for your application 🫡
Understand the Role: Read the job description carefully to understand the key responsibilities and required skills for the Data Warehouse Engineer position. Highlight your experience with SQL, data warehousing, and Power BI in your application.
Tailor Your CV: Customise your CV to reflect your relevant experience and skills that align with the job requirements. Use specific examples of past projects or roles where you successfully utilised SQL and Power BI.
Craft a Compelling Cover Letter: Write a cover letter that showcases your enthusiasm for the role and the company. Mention how your background makes you a great fit for taking ownership of their centralised data platform.
Proofread Your Application: Before submitting, thoroughly proofread your CV and cover letter for any spelling or grammatical errors. A polished application reflects your attention to detail, which is crucial for a Data Warehouse Engineer.
How to prepare for a job interview at SF Recruitment (Tech)
✨Brush Up on SQL Skills
Make sure you're comfortable with SQL queries, as this is a key requirement for the role. Practise writing complex queries and be prepared to discuss your previous experiences using SQL in data warehousing projects.
✨Familiarise Yourself with Data Warehousing Concepts
Understand the fundamentals of data warehousing, including ETL processes, data modelling, and data integration. Be ready to explain how you've applied these concepts in past roles or projects.
✨Showcase Your Power BI Expertise
Since Power BI is mentioned in the job description, prepare to demonstrate your proficiency with it. Bring examples of dashboards or reports you've created and be ready to discuss how they added value to your previous employers.
✨Emphasise Team Collaboration
This role requires working closely with others, so highlight your teamwork skills. Share examples of how you've successfully collaborated with colleagues in the past, especially in a data-driven environment.
