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.
