Data Architect (Relational, Graph s Hierarchical

Modelling)

Key Responsibilities

 Architectural Leadership: Finalize end-to-end data architectures and technical

roadmaps, ensuring they meet the requirements of a high-concurrency, multi-client

application environment.

 Graph s Hierarchical Modelling: Design and implement advanced hierarchical data

structures using Neo4j, transitioning traditional relational data into high-performance

graph models for complex relationship mapping.

 Centralized Metric Hub: Build and govern a centralized "Metric Store" (Headless BI)

that ensures a single source of truth for KPIs across Power BI dashboards and external

API-driven applications.

 Security s Governance: Implement PBAC (Policy-Based Access Control) engines to

manage granular data access dynamically based on user attributes and organizational

policies.

 Hybrid Data Engineering: Orchestrate data flows across a diverse stack

including Databricks (Lakehouse), PostgreSQL, and SQL Server.

 Project Management: Manage project timelines, lead technical sprints, and mentor

developers to ensure delivery against the architectural vision.

Required Technical Expertise

 Graph Databases: Expert-level knowledge of Neo4j (Cypher, Graph Data Science) for

modeling complex hierarchies and networks.

 Data Platforms: Proven experience with Databricks (Spark, Delta Lake) and managing

both relational stores (SQL Server, PostgreSQL).

 BI s Visualization: Deep understanding of Power BI integration, specifically connecting

to semantic models and metric layers.

 Access Control: Hands-on experience with PBAC or Attribute-Based Access Control

(ABAC) frameworks for enterprise security.

 Application Integration: Experience designing APIs or data layers that serve both

analytical tools and transactional applications.