Database Engineer

Rubamin Private Limited; Vadodara; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Rubamin Private Limited seeks a senior database architect to design and manage enterprise-scale data platforms across relational and NoSQL stores, with cloud hosting on AWS, GCP, or Azure.

You will enable AI-driven semantic search, DAM integrations, secure RBAC, backups, and automated ETL/ELT pipelines while collaborating with web teams to ensure fast API access and robust data governance.

Qualifications

• Extensive experience in database architecture across relational and non-relational models.
• Proven ability to deploy and maintain cloud-based multi-database environments.
• Experience with AI-enabled semantic search and DAM integration.
• Strong security, RBAC, encryption, backups, and audit logging.
• Strong scripting and DevOps skills for automation.

Responsibilities

• Architect, deploy, and manage multi-database environments in the cloud (AWS / GCP / Azure).
• Oversee relational databases (MySQL / PostgreSQL) for transactional systems and conservation records.
• Manage NoSQL graph models (MongoDB, DynamoDB, Neo4j) for provenance timelines and metadata.
• Set up vector/hybrid search databases (pgvector, Pinecone, Milvus, Elasticsearch/OpenSearch) for semantic search.
• Collaborate with web developers to ensure low-latency API queries and reliable publishing pipelines.
• Implement caching (Redis, Memcached) for high web traffic.
• Enforce RBAC, encryption, audit logging, backups, and data governance.

Skills

MySQL

PostgreSQL

MongoDB

DynamoDB

Neo4j

pgvector

Pinecone

Milvus

Elasticsearch/OpenSearch

AWS

GCP

Azure

Terraform

CloudFormation

Docker

Python

Bash

Node.js

RBAC

Encryption

Backups

Audit Logs

Tools

Redis

Memcached

CI/CD pipelines

Job description

Role & responsibilities

1. Database Architecture & Cloud Hosting

• Architect, deploy, and manage multi-database environments in the cloud (AWS / GCP / Azure).
• Oversee relational databases (MySQL / PostgreSQL) for transactional systems, object relationships, and conservation records.
• Manage NoSQL document and graph models (MongoDB, DynamoDB, Neo4j, or similar) to represent complex provenance timelines and flexible museum metadata (CDWA, Spectrum, LIDO standards).
• Configure database instances for high availability, auto-scaling, disaster recovery, and failover support.

2. AI, Semantic Search & Digital Asset Integration

• Set up and maintain Vector / Hybrid Search Databases (e.g., Pinecone, Milvus, Qdrant, or Pgvector) to support AI-powered image similarity search, automated tagging, and natural language semantic queries.
• Optimize database pipelines for processing large binaries and metadata linked with high-res digital assets (DAM) and digitized publication files (Digital Library).

3. Web & API Data Integration

• Partner with full-stack and web developers revamping the museum's public website and digital library to ensure low-latency API queries and reliable web publishing pipelines.
• Implement database caching strategies (e.g., Redis, Memcached) for heavy web traffic.

4. Data Security, Provenance & Rights Management

• Enforce strict role-based access control (RBAC), data encryption (at rest and in transit), and audit loggingcritical for sensitive rights management and high-value artwork provenance.
• Establish automated backup procedures, data archiving policies, and business continuity plans.

5. Monitoring, Performance Tuning & Maintenance

• Monitor query performance, indexes, and database health; optimize complex queries and schema structures.

Lead data migration, ingestion scripts, and ETL/ELT pipelines for bulk catalog import from legacy systems

Preferred candidate profile

Domain

Required Skills & Experience

Experience

47+ years in Database Administration, Data Engineering, or Systems Architecture.

Relational DBs

Deep expertise in MySQL or PostgreSQL (schema design, indexing, performance tuning, replication).

NoSQL & Graph DBs

Hands-on experience with MongoDB, DynamoDB, or graph databases (Neo4j) for flexible/nested structures.

Vector / Search Tech

Familiarity with vector databases (pgvector, Pinecone, Milvus, Elasticsearch/OpenSearch) for semantic search setups.

Cloud Platforms

Cloud database management (AWS RDS, Aurora, DynamoDB, GCP Cloud SQL, or Azure Database Services).

DevOps & CI/CD

Infrastructure-as-Code (Terraform, CloudFormation), Docker, basic script automation (Python, Bash, Node.js).

Security & Compliance

Experience with encryption standards, database backups, audit logs, and access management.