Data Platform Solution Architect

Experience & Technical Skills:

• Minimum 7–10 years of experience in data platform architecture.
• Experience in designing cloud-based platforms (preferably Azure).
• Strong knowledge of Azure (networking, security, identity, cost management), Azure Databricks, data integration (batch & streaming), Azure DevOps, CI/CD, and Infrastructure as Code.
• Experience with tools and concepts related to Data Governance and metadata management (e.g., Collibra), data quality and observability.

Architectural Competencies:

• Strong system thinking and long-term architectural mindset.
• Experience in balancing domain autonomy vs. central control.
• Deep understanding of non-functional requirements: security, performance, availability, cost.

Soft Skills:

• Ability to clearly communicate with both technical and business stakeholders (including senior management).
• Strong decision-making skills and ability to defend architectural decisions.
• Maturity in working within a complex, regulated corporate environment.
• English level: C1.

Data Platform Architecture:

• Define and maintain the target architecture of the data platform (ingest, storage, processing, serving, governance, observability).
• Design architecture based on Lakehouse / Medallion architecture with clearly defined layers and responsibilities.
• Establish architectural standards, patterns, and guardrails for platform and domain teams.
• Make key architectural decisions regarding technologies, integrations, and platform evolution.

Data Mesh & Domain Platform:

• Ensure the platform architecture supports autonomy of domain teams, the concept of Data Products and data contracts, scaling of Data Mesh initiatives across the organization, design the platform as an enabler, not a bottleneck for domains.

Security, Access & Compliance:

• Design a security-by-design architecture, including data access control implemented at the data platform level, segregation by layers and data scope, standard access at table and view level, column-level masking in special cases.
• Ensure the architecture complies with regulatory requirements, compliance standards, risk and audit requirements.

Collaboration with NN Group & Data Governance (Key Requirement):

• Closely collaborate with NN Group in terms of alignment of local architecture with group standards and reference data architecture, adoption and local adaptation of centrally developed platform components (L1/L2), participation in group-level architectural initiatives and decision forums.
• Work closely with Data Governance functions (locally and within the group), including embedding governance requirements into architecture (governance by design), supporting metadata management, lineage, data quality, and access management, co-defining standards for Data Products within the Data Mesh model.
• Act as a bridge between NN Group strategy and standards, local business needs, technical teams (Platform, Data Engineering, Security).

Technical Collaboration:

• Work closely with Platform Engineers, Data Engineers, Data Architects / Data Modelers, Security, Risk, and Compliance teams.
• Act as the design authority for platform and cross-domain solutions.