Data Platform Engineer

at  KPMG

JOB DESCRIPTION

We are seeking a skilled Data Platform Engineer with expertise in the Microsoft cloud technology stack to join our professional services team. This role involves building and delivering scalable, secure, and high-performing data platforms for our clients using Microsoft Fabric, Databricks, and other modern data technologies. The ideal candidate will have experience in data platform engineering, data governance, and solution delivery.

YOUR EXPERIENCE

At KPMG, we believe that diversity of thought, background and experience strengthens relationships and delivers meaningful benefits to our people, our clients, and communities. To be considered for this opportunity, your qualifications, skills & experience should include:

• Experience implementing data platforms on the Microsoft cloud stack (Azure Synapse Analytics, Microsoft Fabric, Databricks, Azure Data Lake, Azure Data Factory, Azure SQL, Power BI, etc.).
• Knowledge of data engineering practices, including ELT/ETL, data pipelines, and orchestration tools.
• Understanding of data modeling, data governance, and data security best practices.
• Familiarity working in a systems integrator or professional services environment.
• Proficiency in programming and scripting languages like SQL, Python, and Spark.
• Microsoft certifications (e.g., Azure Data Engineer Associate) are desirable.

• Implement data solutions, including data ingestion, transformation, storage, and visualization layers using Microsoft Fabric, Databricks, Azure Data Services, and related technologies.
• Develop and maintain data pipelines and data integration processes.
• Collaborate with clients to gather requirements, assess current data environments, and support data strategies and roadmaps.
• Ensure solutions align with industry best practices, security standards, and compliance requirements.
• Provide technical guidance and collaborate with development teams.
• Create technical documentation and assist in the development of data governance frameworks and strategies for data quality, lineage, and access management.
• Utilize Microsoft Purview for data governance tasks such as data classification, lineage tracking, and policy enforcement.
• Drive performance optimization, scalability, and reliability in data platform implementations