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- Tasks: Transform business needs into effective data models while collaborating with stakeholders.
- Company: Join a dynamic team focused on innovative data solutions in a remote setting.
- Benefits: Enjoy the flexibility of remote work and gain valuable experience in data modelling.
- Why this job: Be part of impactful data projects that enhance your skills and career prospects.
- Qualifications: Experience in dimensional modeling and proficiency in SQL are essential.
- Other info: This is a 3.5-month contract role, perfect for gaining hands-on experience.
We are seeking an experienced Dimensional Data Modeler/Analyst for a 3.5 months remote contract. You will play a crucial role in our data projects by translating business needs into effective data models.
Key Responsibilities:
- Collaborate with stakeholders to refine, clarify, and iterate on business requirements.
- Analyze and map Key Performance Indicators (KPIs) to underlying source data.
- Identify, analyze, and document data quality issues, proposing solutions and advising on necessary actions.
- Design and build robust dimensional models.
- Develop and document source-to-target mappings for the dimensional model, including transformation logic.
- Ensure a smooth handover and provide ongoing support to data engineering teams.
Required Skills:
- Proven experience in dimensional modeling.
- Strong data analysis and business analysis capabilities.
- Proficiency in SQL.
Dimensional Data Modeler Analyst employer: Sonra
Contact Detail:
Sonra Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Dimensional Data Modeler Analyst
✨Tip Number 1
Familiarise yourself with the latest trends in dimensional data modelling. Understanding current best practices and tools can give you an edge during discussions with our team.
✨Tip Number 2
Brush up on your SQL skills, as they are crucial for this role. Consider working on sample projects or exercises that involve complex queries to demonstrate your proficiency.
✨Tip Number 3
Prepare to discuss specific examples from your past experience where you've successfully translated business needs into data models. This will showcase your ability to collaborate effectively with stakeholders.
✨Tip Number 4
Think about potential data quality issues you’ve encountered in previous roles and be ready to share how you addressed them. This will highlight your analytical skills and problem-solving abilities.
We think you need these skills to ace Dimensional Data Modeler Analyst
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities of a Dimensional Data Modeler/Analyst. Familiarise yourself with dimensional modeling concepts and how they apply to business needs.
Tailor Your CV: Highlight your relevant experience in dimensional modeling and data analysis. Use specific examples that demonstrate your proficiency in SQL and your ability to collaborate with stakeholders.
Craft a Compelling Cover Letter: In your cover letter, explain why you're a great fit for this role. Mention your experience with KPIs, data quality issues, and any successful projects you've completed that relate to the job description.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter. Check for any spelling or grammatical errors, and ensure that all information is clear and concise.
How to prepare for a job interview at Sonra
✨Showcase Your Dimensional Modeling Experience
Be prepared to discuss your previous projects involving dimensional modeling. Highlight specific examples where you successfully translated business needs into effective data models, as this will demonstrate your expertise and relevance to the role.
✨Understand Key Performance Indicators (KPIs)
Familiarise yourself with common KPIs relevant to the industry. During the interview, be ready to explain how you would analyse and map these KPIs to underlying source data, showcasing your analytical skills and understanding of business requirements.
✨Prepare for Data Quality Discussions
Expect questions about data quality issues. Think of examples from your past work where you identified and resolved data quality problems. Be ready to propose solutions and discuss how you advised teams on necessary actions to improve data integrity.
✨Demonstrate SQL Proficiency
Since proficiency in SQL is a required skill, brush up on your SQL knowledge. Be prepared to answer technical questions or even solve problems on the spot. This will help convey your technical capabilities and confidence in handling data.
