Senior Database / Azure Data Engineer

Location: Dallas, Texas (Onsite)

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 Expertise10–14 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.