Nordic BI Platform Architect: Data Governance & Azure

Lowell; Göteborgs kommun; Hybrid; SEK 900,000 - 1,200,000; Full time

Job summary

Lowell is seeking a BI Architect for its Nordic region, collaborating with Data teams and stakeholders across Denmark, Finland, Sweden and Norway. You will define and govern scalable data platform and analytics architecture to support Lowell's Nordic data needs, ensuring secure, well-documented solutions aligned with enterprise principles.

You will translate requirements into robust designs, provide high-level and low-level documentation, and ensure data landscape supports scalability,

Qualifications

• 5+ years of experience in Business Intelligence or Data Management and Platform Architecture.
• Strong understanding of BI architecture and data warehousing.
• Hands-on experience with Azure, Databricks, Synapse and Data Factory.
• Knowledge of GDPR, security and compliance in BI platforms.

Responsibilities

• Own and guide BI platform design and architecture standards.
• Ensure BI solutions are scalable, secure, and cost-efficient.
• Define and maintain architecture documentation and standards.
• Provide technical leadership and architectural guidance to BI teams.
• Drive data governance, access management, data quality, lineage and ownership.
• Embed GDPR, security and compliance in BI platforms.
• Lead decisions on data protection and platform security.

Skills

BI architecture

Data modelling

Azure

Databricks

Synapse

Data Factory

Data governance

English

Finnish

Education

Degree in software engineering or computer science

Tools

Azure Databricks

Azure Synapse

Azure Data Factory

Data Lake

Job description

Lowell is seeking a BI Architect for its Nordic region, collaborating with Data teams and stakeholders across Denmark, Finland, Sweden and Norway. You will define and govern scalable data platform and analytics architecture to support Lowell's Nordic data needs, ensuring secure, well-documented solutions aligned with enterprise principles.

You will translate requirements into robust designs, provide high-level and low-level documentation, and ensure data landscape supports scalability,