Role & 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 eventdriven 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. • Design secure MCP-based integration patterns to expose enterprise data, APIs, metadata, documents, and tools to AI assistants and agentic workflows. • Own data quality, reconciliation, metadata, lineage, data freshness, and source-totarget control frameworks. • Optimize analytical workloads across ClickHouse, warehouse queries, pipelines, dashboards, reporting layers, and AI retrieval workloads. • Support OLTP performance engineering across PostgreSQL, MongoDB, Redis, Elasticsearch, and high-concurrency application workloads. • Define security, access control, masking, audit logging, retention, compliance, HA, DR, backup, restore, observability, and capacity planning standards. • Drive modernization from legacy databases, fragmented reporting systems, and siloed data marts to a scalable enterprise data and AI-ready platform.

📌 Enterprise Data Architect (Mumbai)
🏢 Uberlife Consulting
📍 Mumbai