Principal Data & AI Consultant

A senior engineering leader based in Hyderabad, India, the Principal Data & AI Consultant at Microsoft leads the successful technical execution and delivery of complex client projects across diverse domains. Acting as a strategic anchor among clients, architects, delivery managers, project managers, and delivery teams, this role embeds AI-native thinking into delivery models to ensure intelligent, scalable solutions aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates broad expertise, and advocates for client-value-driven solutions.

Responsibilities

• AI-First Delivery Leadership: embed AI-first principles into delivery workflows, drive end-to-end delivery of complex projects, and ensure solutions are scalable, robust, and aligned with client outcomes. develop reusable components, accelerators, and scalable architectures; oversee technical execution across multiple projects; collaborate with clients and stakeholders to define strategies, plans, milestones, and risk mitigation; translate business requirements into scalable technical solutions; optimize delivery models for modern AI-native execution with automation and intelligent processes; assess at-risk projects and establish credible recovery paths.
• Engineering Excellence: champion high-quality engineering practices, maintain coding standards and architectural integrity, and set guardrails for secure coding, test-driven development, observability, and performance. Promote continuous learning, certifications, and the adoption of Agile, DevOps, and CI/CD to deliver robust, scalable solutions; foster a culture of technical rigor, innovation, and accountability.
• Innovation & Thought Leadership: apply design thinking to user-centric solutions, monitor emerging technologies, and lead innovation in delivery models, reusable assets, and accelerators; drive modern thinking and best practices across teams to support continuous improvement.
• Client Engagement & Solutioning: engage with clients to understand business needs, provide expert guidance throughout the project lifecycle, support pre-sales with estimations and proofs-of-concept, and build strong client relationships to ensure satisfaction and value delivery; partner with client leadership to enable AI-native operations, focusing on user adoption and workflow transformation.
• Team Management & Mentorship: lead and mentor cross-functional teams, conduct performance reviews, and support professional development; foster learning, collaboration, and technical excellence.
• Quality & Compliance: ensure secure, compliant, and reliable delivery through secure coding, test-driven development, observability, design reviews, and quality gates across engagements.
• Strategic Partnering: serve as a strategic partner for internal and external stakeholders, provide guidance and execution oversight to align with organizational goals, and define and track business KPIs such as revenue uplift, cost reduction, and customer satisfaction linked to AI initiatives.

Requirements

• 20+ years of software/solution engineering experience, with 3–5+ years in delivery leadership roles; proven track record delivering complex, multi-disciplinary projects.

• Strong understanding of modern delivery methodologies (Agile, Scrum, DevOps, etc.) and excellent communication, stakeholder management, problem-solving, and team leadership skills.

• Bachelor’s degree in computer science, engineering, or a related field (or equivalent experience); relevant certifications are a plus.

• Areas of expertise include:

• Enterprise Data Architecture & Modern Platforms: lead data modernization initiatives, define architectures with metadata, lineage, classification, and data discovery capabilities, and drive decisions for modern data platforms (Microsoft Fabric, Purview, Azure Synapse Analytics, Azure Data Factory, and partner platforms), balancing performance, scalability, resilience, and total cost of ownership.

• Data Engineering & Large-Scale Data Processing: hands-on leadership for designing and operating large batch and streaming pipelines (Spark, Databricks, Kafka, Hadoop, Hive, HDInsight); own data engineering standards, SLAs/SLOs, and performance targets; drive DataOps practices.

• Database Platforms, Performance & Capacity Engineering: hands-on expertise with Azure SQL, SQL Server, PostgreSQL, MySQL, MariaDB, Oracle, Teradata, Netezza, Cosmos DB, and columnar databases.

• Location: Hyderabad, Telangana, India