Microsoft Fabric Data Engineer
Microsoft Fabric Data Engineer

Microsoft Fabric Data Engineer

Full-Time 55000 - 70000 £ / year (est.) No home office possible
Dynatechconsultancy

At a Glance

  • Tasks: Build and manage data pipelines using Microsoft Fabric for analytics platforms.
  • Company: Join a forward-thinking tech company focused on data innovation.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Dynamic role with potential for career advancement in data engineering.
  • Why this job: Make an impact by optimising data processes and collaborating with diverse teams.
  • Qualifications: Experience with Microsoft Fabric and strong analytical skills required.

The predicted salary is between 55000 - 70000 £ per year.

We are looking for a Microsoft Fabric Data Engineer to build and manage data pipelines and analytics platforms. You will work closely with architects and business teams to ensure reliable, high-performance data processing and reporting capabilities.

Key Responsibilities

  • Design and build data pipelines using Microsoft Fabric
  • Develop data transformation and processing workflows
  • Ensure data quality, consistency, and reliability across systems
  • Collaborate with analytics teams to support reporting requirements
  • Optimize performance of data pipelines and storage systems
  • Support integration with Dynamics 365 and other enterprise systems
  • Monitor and troubleshoot data-related issues
  • Maintain documentation for data processes and workflows
  • Stay updated with Microsoft Fabric features and enhancements

Required Skills & Qualifications

  • Strong experience with Microsoft Fabric or similar data platforms
  • Knowledge of ETL/ELT processes and data pipeline development
  • Experience working with large datasets and distributed systems
  • Strong analytical and problem-solving skills
  • Ability to collaborate with cross-functional teams

Preferred Qualifications

  • Experience with Power BI and data visualization tools
  • Familiarity with Azure data services

Experience

  • 4–7 years of experience in data engineering

Education

  • Bachelor’s degree in Computer Science, Data Engineering, or related field

Microsoft Fabric Data Engineer employer: Dynatechconsultancy

Join a forward-thinking company that values innovation and collaboration, where as a Microsoft Fabric Data Engineer, you will have the opportunity to work with cutting-edge technology in a dynamic environment. Our supportive work culture fosters professional growth, offering continuous learning opportunities and the chance to collaborate with talented teams on impactful projects. Located in a vibrant area, we provide a stimulating workplace that encourages creativity and rewards excellence.
Dynatechconsultancy

Contact Detail:

Dynatechconsultancy Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Microsoft Fabric Data Engineer

✨Tip Number 1

Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Microsoft Fabric. A friendly chat can lead to insider info about job openings or even referrals.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your data pipelines and analytics projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.

✨Tip Number 3

Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss ETL/ELT processes and how you've tackled data quality issues in the past. Confidence is key!

✨Tip Number 4

Don't forget to apply through our website! We love seeing applications directly from candidates who are passionate about data engineering and Microsoft Fabric. It shows initiative and enthusiasm!

We think you need these skills to ace Microsoft Fabric Data Engineer

Microsoft Fabric
Data Pipeline Development
ETL/ELT Processes
Data Transformation
Data Quality Assurance
Performance Optimisation
Dynamics 365 Integration
Troubleshooting Data Issues
Documentation Skills
Power BI
Data Visualisation Tools
Azure Data Services
Analytical Skills
Problem-Solving Skills
Collaboration Skills

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights your experience with Microsoft Fabric and data engineering. We want to see how your skills match the job description, so don’t be shy about showcasing relevant projects or achievements!

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the role and how your background makes you a perfect fit. We love seeing genuine enthusiasm for what we do at StudySmarter.

Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled challenges in data processing or pipeline development. We value analytical thinkers who can navigate complex issues, so let us know how you’ve made an impact!

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts!

How to prepare for a job interview at Dynatechconsultancy

✨Know Your Microsoft Fabric Inside Out

Make sure you brush up on your knowledge of Microsoft Fabric and its features. Be ready to discuss how you've used it in past projects, especially in building data pipelines and managing analytics platforms.

✨Showcase Your ETL/ELT Expertise

Prepare to talk about your experience with ETL and ELT processes. Have specific examples ready that demonstrate your ability to design and implement data transformation workflows effectively.

✨Collaboration is Key

Since the role involves working closely with architects and business teams, think of examples where you've successfully collaborated with cross-functional teams. Highlight your communication skills and how they contributed to project success.

✨Problem-Solving Mindset

Be prepared to discuss how you've tackled data-related issues in the past. Think of specific challenges you've faced with large datasets or distributed systems and how you resolved them, showcasing your analytical skills.

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