Senior Technical Consultant/ Manager - Microsoft Azure & Microsoft Fabric Data Engineer

KPMG

KPMG offers an opportunity to be part of a dedicated team that transforms insights into opportunities globally. The Microsoft team at KPMG is experiencing high client demand, aiming to help clients leverage Microsoft Fabric for business transformation. This role involves working with advanced technologies, tackling complex data tasks, and contributing to business growth in a diverse environment.

In this role you can expect to have the responsibilities:

• Design and develop enterprise-level data solutions using Microsoft Fabric and Azure.
• Participate in data architecture solution planning and implementation.
• Develop complex data models adhering to standards.
• Manage data ETL processes from multiple sources for analytics.
• Support pre-sales through demonstrations and asset building.
• Stay updated on data technologies, trends, and recommend optimizations.

This role comes with the following benefits:

• Inclusive and barrier-free work environment.
• Diverse workforce commitment.
• Support for personal and professional development.

This role requires you to have:

• 5+ years in data architecture and engineering consulting.
• Experience with large-scale data architectures and engineering solutions.
• Pre-sales support expertise for data solutions.
• Proficiency in data integration, quality, profiling, and cleansing.
• Power BI for BI visualizations and reports.
• SQL and Python proficiency.
• Business acumen to translate requirements into technical solutions.
• Excellent communication skills.

You would benefit from having:

• Hands-on experience with Azure Data Factory, Synapse, Data Lake or Databricks.
• Knowledge of Microsoft Fabric.

KPMG values integrity, excellence, courage, teamwork, and commitment to meaningful actions. The company is an equal opportunity employer, supporting an inclusive workplace where diversity thrives. KPMG provides adjustments or accommodations during the recruitment process to ensure all candidates can perform optimally.