Associate Principal - Data Engineering

Key Responsibilities

• Design and develop scalable high-performance database solutions.
• Lead initiatives in data modeling, database design, and performance tuning.
• Implement and manage Role-Based Access Control (RBAC) and ensure database security 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.
• Work with frameworks such as DBT, FastAPI, or Django to enable data transformation and service exposure.
• Integrate data platforms with LLM-based systems and agentic workflows for 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: 8-10 years of experience as a Database Engineer/Data Engineer.
• Data Modeling and Database Design: Strong expertise in data modeling and database design.
• Performance Tuning and Optimization: Proven experience writing complex SQL/T-SQL queries, stored procedures, functions, and triggers.
• Advanced SQL and T-SQL: Strong knowledge of database internals, indexing strategies, and execution plans.
• Security Models and RBAC: Good understanding of Azure ecosystem and services, including networking fundamentals in Azure VNETs, private endpoints, etc.
• Azure Data Engineering: 5 years of experience with Azure data platforms including Azure Data Factory, building complex pipelines and orchestrations, Azure Synapse Analytics, Microsoft Fabric, data lakes, and data warehouse implementations.
• Programming Frameworks: Strong hands-on experience in Python including API integrations and data processing, building microservices architectures.
• AI/LLM Agentic Systems: Familiarity with AI-powered automation workflows, working with LLM-based interfaces, and designing agent-based solutions.

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.
• Autonomous or semi-autonomous workflow design.

Other Details

Variable Compensation: This position includes a bonus or variable payout component based on individual and organizational performance. Actual compensation within the range will be dependent upon the individual's skills, experience, performance, and internal equity.

Benefits/Perks: Comprehensive Medical Plan, Short Term and Long-Term Disability Coverage, 401(k) Plan with Company match, Life Insurance, Vacation Time, Sick Leave, Paid Holidays, Paid Paternity and Maternity Leave.

The range displayed on each job posting reflects the minimum and maximum salary target for the position across all US locations. Within the range, individual pay is determined by work location and job level and additional factors including job-related skills, experience, and relevant education or training.

Disclaimer: The compensation and benefits information provided herein is accurate as of the date of this posting. LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our employment decisions are made without regard to race, color, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family-care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law.