Enterprise Data Platform Architect

Key Responsibilities :

- Design and govern enterprise data architecture across OLTP systems, Data Warehouse, Data Lake, ClickHouse, Kafka, and reporting platforms.

- Own Data Warehouse and Data Lake architecture including raw, curated, trusted, data mart, semantic, and consumption layers.

- Define standards for facts, dimensions, aggregates, materialized views, semantic layers, partitions, historical data, and analytical data marts.

- Design OLTP data models for high-volume applications such as trading, CRM, account opening, client platforms, partner platforms, and operations.

- Review transactional schema design, indexing, partitioning, archival, retention, and data access patterns across PostgreSQL and MongoDB.

- Architect Kafka, CDC, ETL, and ELT pipelines for batch, near real-time, and event-driven data movement.

- Ensure integration between PostgreSQL, MongoDB, Redis, Elasticsearch, Kafka, ClickHouse, Data Warehouse, and Data Lake platforms.

- Define AI-ready data architecture for RAG, semantic search, embeddings, vector stores, enterprise knowledge access, and AI agent consumption.

- Guide architecture for vector databases / vector search using platforms such as PostgreSQL pgvector, MongoDB Vector Search, Elasticsearch vector search, or similar tools.