Technology Engineer - MSSQL + Vector DB

We are looking for an experienced Technology Engineer with strong expertise in Microsoft SQL Server (MSSQL) and hands-on experience with Vector Databases. The ideal candidate will be responsible for designing, implementing, and optimizing database solutions that support high-performance, large-scale applications, while also leveraging vector databases for AI/ML-driven workloads.

Key Responsibilities

• Design, implement, and maintain MSSQL databases to ensure high availability, performance, and security.
• Develop and optimize complex queries, stored procedures, triggers, and functions.
• Implement backup, recovery, and disaster recovery strategies.
• Work with Vector Databases (such as Pinecone, Weaviate, Milvus, Chroma, or similar) to support AI/ML and semantic search use cases.
• Optimize data pipelines and indexing strategies for high-performance data retrieval.
• Collaborate with application development teams to design scalable and efficient database solutions.
• Monitor, troubleshoot, and resolve database performance issues.
• Ensure compliance with security, regulatory, and data governance policies.
• Stay updated on emerging trends in database technologies, particularly in vector search and AI-driven data management.

Required Skills & Experience

• 5 to 7 years of professional experience in database engineering/administration.
• Strong expertise in MSSQL Server (installation, configuration, optimization, replication, clustering, performance tuning).
• Hands-on experience with at least one Vector Database (e.g., Pinecone, Weaviate, Milvus, Chroma, Vespa, Qdrant).
• Proficiency in SQL programming and database design principles.
• Strong knowledge of ETL processes, data pipelines, and integration with applications.
• Experience with cloud environments (Azure, AWS, or GCP) and managed database services.
• Familiarity with AI/ML workloads, semantic search, and embeddings-based data retrieval is a plus.
• Excellent problem-solving, analytical, and communication skills.

Good to Have

• Knowledge of NoSQL databases (MongoDB, Cassandra, etc.).
• Exposure to Python or Java for integration with vector DBs.
• Experience with Kubernetes and containerized database deployments.