Key Responsibilities :

- Design and define scalable, secure, and high-performance enterprise data architectures aligned with business and technology requirements.

- Lead the design and implementation of knowledge graph solutions, including ontology, taxonomy, and semantic data models.

- Develop and implement graph-based data solutions using RDF, OWL, SPARQL, Neo4j, and property graphs.

- Define and implement Master Data Management (MDM) and entity resolution strategies to ensure data consistency and accuracy.

- Design conceptual, logical, physical, and dimensional data models for enterprise applications and analytics platforms.

- Architect and optimize modern data platforms using PostgreSQL, pgvector, Azure SQL, Databricks, and Snowflake.

- Define scalable data pipelines and ETL/ELT frameworks for data ingestion, transformation, integration, and processing.

- Establish data security and access-control mechanisms, including row-level security, data classification, and secure data access.

- Define and enforce data governance, data quality, metadata, and data management standards across the organization.

- Design and implement cloud-native data solutions across Microsoft Azure and AWS.

- Collaborate with engineering teams to deploy and manage data workloads using Kubernetes and Terraform.

- Provide technical leadership in architecture decisions, solution design, technology evaluation, and implementation planning.

- Work closely with data engineers, application architects, DevOps, security, and business stakeholders to deliver scalable data solutions.

- Review existing data architectures and identify opportunities for modernization, optimization, and cost efficiency.

- Provide technical guidance and mentorship to data engineering and architecture teams.

Key Skills :

- Strong experience in Enterprise Data Architecture and data modelling.

- Hands-on experience with Knowledge Graphs, Ontology, and Taxonomy.

- Strong knowledge of RDF, OWL, and SPARQL.

- Hands-on experience with Neo4j and Property Graphs.

- Strong understanding of Master Data Management (MDM) and Entity Resolution.

- Experience with Dimensional Modelling and enterprise data modelling techniques.

- Strong hands-on experience with PostgreSQL, pgvector, and Azure SQL.

- Experience with modern data platforms such as Databricks and Snowflake.

- Strong understanding of Data Pipelines, ETL/ELT, and data integration.

- Experience with Data Governance, Data Quality, Metadata Management, and Data Security.

- Strong knowledge of Row-Level Security and data access-control mechanisms.

- Experience with Kubernetes and Terraform.

- Strong cloud experience with Microsoft Azure and AWS.

- Good understanding of cloud-native and distributed data architectures.

- Strong technical leadership, communication, problem-solving, and stakeholder management skills.