Description

Key Responsibilities

• Design, develop, and maintain scalable, high-performance database solutions.
• Lead data modelling, database design, and performance-tuning initiatives.
• Develop and optimize complex SQL/T-SQL queries, stored procedures, functions, and triggers.
• Implement and manage Role-Based Access Control (RBAC) while ensuring database security and compliance.
• Analyze and improve database internals, indexing strategies, and execution plans.
• Build and manage end-to-end data pipelines using Azure Data Factory.
• Design and implement modern data architectures, including data warehouses and data lakes using Azure Synapse and Microsoft Fabric.
• Collaborate with cross-functional teams to deliver scalable data engineering and analytics solutions.
• Develop and maintain Python-based data services, APIs, and microservices.
• Use frameworks such as DBT, FastAPI, or Django to support data transformation and service exposure.
• Integrate data platforms with LLM-based systems and agentic workflows to enable intelligent automation.
• Contribute to the design and implementation of agentic AI solutions, including orchestration, tool usage, and API interaction patterns.

Required Qualifications

Database Engineering Expertise

• 10–14 years of experience as a Database Engineer or Data Engineer.
• Strong expertise in data modelling, database design, performance tuning, optimization, advanced SQL, and T-SQL.
• Proven experience writing complex stored procedures, user-defined functions (UDFs), and triggers.
• Strong knowledge of database internals, indexing, execution plans, security models, and RBAC.

Azure Data Engineering

• 5+ years of experience with Azure data platforms.
• Hands-on experience building complex pipelines and orchestrations using Azure Data Factory (ADF).
• Experience with Azure Synapse Analytics, Microsoft Fabric, data lakes, and data warehouse implementations.
• Good understanding of the Azure ecosystem, core services, and networking fundamentals such as VNets and private endpoints.

Programming and Frameworks

• Strong hands-on experience in Python for API integrations, data processing, and microservices architecture.
• Familiarity with DBT (Data Build Tool), workflow orchestration tools, and frameworks such as FastAPI or Django.

AI, LLM, and Agentic Systems

• Experience working with LLM-based interfaces and AI-powered automation workflows.
• Hands-on exposure to Claude or similar agentic coding frameworks.
• Experience designing and building agent-based solutions.
• Understanding of prompt engineering, tool orchestration, API-based LLM integrations, and autonomous or semi-autonomous workflow design.

Preferred Qualifications

• Experience implementing AI-driven data solutions.
• Exposure to MLOps or AI lifecycle management.
• Familiarity with distributed systems and event-driven architectures.
• Strong problem-solving and analytical skills.

Soft Skills

• Excellent communication and stakeholder management skills.
• Ability to work effectively in a fast-paced, collaborative environment

Key Skills

Education

Any Graduate