EH - MS Fabric Sr. Engineer - 102

As an EH - MS Fabric Sr. Engineer at our company, you'll lead the design and development of scalable data solutions utilizing Microsoft Fabric and Power BI. Your responsibilities will include configuring Azure Data Factory pipelines, scripting in SQL and Python for automation, and ensuring the performance and reliability of these projects. You'll collaborate with cross-functional teams to understand their data needs and mentor junior engineers, while also keeping an eye on industry trends to continuously enhance our data management practices.

To be considered for the EH - MS Fabric Sr. Engineer role, candidates should hold a Bachelor's degree in Computer Science, Information Technology, or a related field, with a Master's degree preferred. Experience is key, as we require at least 5 years in data architecture and development using Microsoft Fabric and Azure services. Proficiency in database design, along with strong analytical skills and the ability to communicate technical concepts effectively, are also vital.

An EH - MS Fabric Sr. Engineer can significantly enhance our data capabilities by designing advanced analytics solutions and optimizing data pipelines. Your expertise in Microsoft Fabric and Azure services will guide the development of efficient data models and ETL processes. Additionally, by mentoring younger colleagues and staying updated on industry trends, you will help foster a forward-thinking approach to our data management and analytics strategies.

Key technical skills for an EH - MS Fabric Sr. Engineer include deep expertise in Microsoft Fabric architecture and Azure services, solid experience with data architecture principles, and proficiency in SQL and Python for scripting and automation. Familiarity with Power BI for data visualization and experience managing CI/CD pipelines will also be crucial for ensuring smooth developments and deployments within our data environments.

In the EH - MS Fabric Sr. Engineer role, you can expect a collaborative and innovative team environment where cross-functional teamwork is highly valued. You'll be working alongside talented professionals who are willing to share knowledge and best practices, and you will have the opportunity to lead and mentor others. We encourage continuous learning, so staying updated with the latest tools and techniques in data management is strongly supported within our culture.

Absolutely! When answering this question, emphasize your specific projects where Microsoft Fabric was key to creating scalable data solutions. Discuss the architecture you designed, any challenges you faced, and how you overcame them, all while ensuring it ties back to the business outcomes.

To address this, discuss specific methodologies you employ such as performance testing, tuning of data pipelines, and utilizing Azure monitoring tools. Explain how these practices help you proactively identify and resolve potential performance bottlenecks.

When answering this question, detail how you use Azure Data Factory for creating and managing data pipelines. Provide examples of how setting up efficient ETL processes through ADF has streamlined data integration and processing in your previous roles.

In your answer, outline the types of automation you've implemented with SQL and Python, such as data cleaning, transformation, and reporting. Including specific scripts or methodologies can demonstrate your technical skills and familiarity with process automation in data engineering.

Articulate your process of engaging with stakeholders to gather their data needs, and illustrate how you translate these into technical specifications. You might mention the importance of feedback loops and iterative development in ensuring that the final solution aligns with business objectives.

When discussing mentoring, share specific strategies such as pairing them with projects, conducting knowledge-sharing sessions, or providing access to learning resources. Highlight your focus on fostering a culture of continuous learning within the team.

Here, talk about specific challenges you've faced—like data redundancy or mismatched schemas—and discuss the solutions you implemented, showcasing your problem-solving skills and flexibility while adapting to evolving data needs.

Mention your engagement in professional communities, attending conferences, subscribing to relevant publications, or taking online courses. This demonstrates your proactive attitude towards learning and staying ahead in a rapidly changing field.

Explain how you leverage CI/CD pipelines for deployment and integration of data solutions, which enhances collaboration and reduces the risk in deploying new features. Discuss how frequent integration can help catch issues early and streamline the release process.

Discuss methods such as regular data audits, validation checks, and implementing robust error-handling processes. Emphasize a systematic approach you take to maintain data accuracy and reliability throughout the data lifecycle.