Senior Data Platform Lead & Architect

KPMG Norway

Oslo fylke

On-site

NOK 1,000,000 - 1,500,000

Full time

38 hours ago

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Job summary

KPMG Norway is seeking an experienced Data Platform Lead to own and modernize internal data and analytics platforms. You will drive architecture, data pipelines, and governance while collaborating with stakeholders across Finance, HR, IT and business functions.

You will shape the data platform strategy, evaluate new technologies, and ensure reliability and security across Azure, Fabric, Databricks and related services. This role blends hands-on delivery with technical leadership.

Qualifications

5+ years of relevant experience in data engineering, data platforms or similar technical roles, preferably with experience taking technical ownership of solutions.
Solid experience with Microsoft Azure and one or more modern data platform technologies, such as Microsoft Fabric or Azure Databricks.
Strong SQL skills and experience with Python and/or PySpark.
Experience designing and developing data pipelines, ETL/ELT processes, data warehouses and lakehouses.
Good understanding of data modeling principles and techniques, including relational and dimensional modeling, normalization, star schemas and the design of analytical data models.
Familiarity with Power BI, semantic models and the requirements of enterprise reporting and analytics.
Experience with cloud platform operations, monitoring, troubleshooting and performance optimization.
Understanding of DevOps practices and tools such as Git, Azure DevOps, CI/CD and infrastructure as Code.
Good understanding of security, identity and access management, data governance and data protection principles.

Responsibilities

Data engineering: Design, develop and optimize reliable data pipelines, data integrations, transformation processes and data models to support reporting, analytics and future AI use cases.
Data modeling and architecture: Design and maintain well-structured, reusable data models, applying appropriate modeling principles and techniques to ensure consistency, scalability, performance and ease of consumption.
Platform operations and maintenance: Ensure the stability, availability and performance of existing solutions by monitoring data flows, troubleshooting incidents, resolving technical issues and proactively improving reliability.
Data quality and governance: Establish and maintain standards for data quality, security, access management, documentation and data lifecycle management.
DevOps and automation: Implement and improve development practices, including version control, CI/CD, automated testing, monitoring and Infrastructure as Code.