We are seeking an experienced Data Architect to design, govern, and scale a secure enterprise data platform supporting analytics and AI workloads. The ideal candidate has strong expertise in relational and distributed data systems, with a focus on performance, high availability, and compliance in regulated or high-security environments.

Key Responsibilities

Design enterprise data architecture, including logical and physical models for structured and unstructured data.
Define and govern multi-layer data architecture (raw, processed, curated/analytics layers).
Establish data governance standards, classification frameworks, and enterprise data ownership models.
Architect solutions across relational databases (PostgreSQL), NoSQL (MongoDB), search/indexing platforms (OpenSearch/Elasticsearch), vector databases (Qdrant/Milvus/Pinecone), and object storage systems (MinIO / S3-compatible).
Define disaster recovery strategies, including RTO/RPO targets, backup policies, replication, and failover architecture.
Design high-availability architectures and clustering strategies for enterprise-scale deployments.
Oversee schema standards, indexing strategies, partitioning models, and performance optimization.
Define data lifecycle management policies: retention, archival, and purging standards.
Ensure audit logging, privileged access tracking, and traceability in line with security requirements.
Define logging standards at the data layer and integrate with centralized monitoring.
Lead capacity planning and scalability strategies for growing data volumes and analytics workloads.
Review and approve data-related changes, schema migrations, and platform enhancements.
Provide architectural oversight and technical leadership to Data Engineering, DevOps, Security, and Analytics teams.

Skills & Requirements

5–7+ years of experience in data architecture or enterprise data engineering.
Strong expertise in relational databases (PostgreSQL).
Experience with NoSQL databases (MongoDB).
Familiarity with search and indexing systems (OpenSearch/Elasticsearch).
Experience with object storage systems (S3-compatible).
Knowledge of distributed systems and high-availability design.
Experience defining RTO/RPO and backup strategies.
Strong understanding of data security, audit logging, and governance principles.

Preferred Qualifications:

Bachelor's Degree in Computer Science, IT, Data Engineering, Software Engineering, or related field.
Master's Degree in Data Engineering, Data Science, Computer Science, Information Systems, or related discipline (preferred).
Experience in on-premises enterprise environments.
Exposure to AI/ML data platforms.
Familiarity with Kubernetes-based deployments.

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