Overview
Microsoft Industry Solutions - Global Center Innovation and Delivery Center (GCID) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GCID presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles.
The Principal Consultant is a senior leader responsible for the successful technical execution and delivery of complex client projects across diverse domains. This role acts as a strategic anchor between clients, architects, delivery managers, project managers, and delivery teams. In the AI-first GCID organization, Principal Consultants are expected to embed AI-native thinking into delivery models, ensuring solutions are intelligent, scalable, and aligned with business outcomes. The ideal candidate is passionate about technology, demonstrates breadth of expertise, and advocates for solutions that deliver true client value.
Responsibilities
AI-First Delivery Leadership
Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes.
Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements.
Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches.
Define and institutionalize engineering guardrails that embed secure coding, test‑driven development, observability, and performance best practices by default.
Innovation & Thought Leadership
Use design thinking to shape user‑centric solutions, aligning business goals, architecture decisions, and delivery execution.
Client Engagement & Solutioning
Team Management & Mentorship
Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence.
Ensure secure, compliant, and reliable solution delivery through secure coding, test driven development, observability, design reviews, and quality gates across all engagements.
Define and track specific Business KPIs (e.g., revenue uplift, operational cost reduction, customer CSAT improvement) associated with AI initiatives.
Qualifications
Enterprise Data Architecture & Modern Platforms
Lead enterprise data modernization initiatives in close collaboration with Enterprise and Solution Architects, spanning architecture assessment, target‑state design, hands‑on implementation, and optimization.
Co‑define architectures with Architects where metadata, lineage, classification, and data discovery are first‑class capabilities, enabling governed, trusted analytics and AI consumption at scale.
Drive and influence architectural decisions for modern data platforms, providing hands‑on delivery leadership across Microsoft Fabric (OneLake, Warehouse, Lakehouse, Event streams, Real‑Time Intelligence), Microsoft Purview, Azure Synapse Analytics, Azure Data Factory, and partner platforms such as Snowflake and Teradata.
Partner with Architects on workload characterization, environment separation, capacity planning, and SKU sizing, balancing performance, scalability, resilience, and total cost of ownership.
Share accountability with Architects for production architectures, owning performance outcomes, operational stability, and long‑term sustainability through continuous optimization and issue resolution.
Data Engineering & Large Scale Data Processing
Handson leadership in designing, building, and operating largescale batch and streaming data pipelines using Apache Spark, Databricks, Kafka, Hadoop, Hive, and HDInsight.
Own data engineering standards, SLAs, SLOs, and performance baselines, while actively implementing and reviewing critical pipelines.
Lead and perform pipeline performance assessments and tuning, including compute sizing, partition strategies, memory optimization, shuffle reduction, and concurrency management.
Drive DataOps practices with direct involvement in monitoring, alerting, capacity scaling, and continuous optimization.
Database Platforms, Performance & Capacity Engineering
Handson expertise across Azure SQL, SQL Server, PostgreSQL, MySQL, MariaDB, Oracle, Teradata, Netezza, Cosmos DB, and columnar analytics engines.
Lead and execute database performance assessments, capacity planning, and workload sizing for transactional, analytical, and AI workloads.
Perform query tuning, execution plan analysis, indexing strategy design, wait state analysis (e.g., CXPACKET), and storage/I/O optimization.
RealTime Analytics & Operational Intelligence
Implement and tune Event streams, KQL databases, real-time dashboards, and ingestion pipelines to meet low latency and high throughput requirements.
Take accountability for real-time workload sizing, Fabric capacity selection, ingestion rate planning, query concurrency, and retention strategies.
AI First Data Engineering & Unify Your Data
Design and implement agentic AI workflows that assist in data discovery, preparation, profiling, validation, and performance optimization.
Actively use large language models to automate data engineering tasks such as schema inference, pipeline generation, metadata enrichment, documentation, and tuning recommendations.
Implement AI powered data wrangling solutions, while maintaining governance, explainability, and human in the loop controls.
Lead the use of AI assistants (agents) to quickly build and improve data pipelines. This includes automating tasks like generating code for data processing, creating tests for quality, and helping to move data from older systems to newer platforms like Microsoft Fabric. The focus is on enabling teams to deliver faster and more reliably.
AI & Advanced Analytics Enablement
Design, implement, and optimize solutions using AI Agents where viable using Azure Machine Learning, Azure OpenAI, and Azure AI Services, including RAG pipelines and inference workloads.
Ensure AI and analytics solutions are grounded in Purview managed metadata and Business Glossary context, improving trust, explainability, and relevance of AI outputs.
Apply Responsible AI principles by leveraging Purview classification, lineage, and sensitivity labels to control data access, usage, and model inputs in production AI systems.
Tune AI systems for retrieval latency, inference performance, concurrency, and cost, using telemetry and real usage patterns.
Embed observability, monitoring, drift detection, and performance metrics into production AI systems.
Design and model cost-efficient AI architectures, balancing performance/latency against consumption costs (e.g., Token optimization, SKU selection, Provisioned vs. Pay-as-you-go)
Implement FinOps governance for AI, establishing budget guardrails, chargeback models, and ROI forecasting for high-consumption workloads.
Data Governance, Trust & Operating Models
Own the hands-on implementation of enterprise data governance using Microsoft Purview, including data cataloging, lineage tracking, classification, sensitivity labeling, and access policy enforcement.
Lead the definition, rollout, and governance of an enterprise Business Glossary, establishing shared business definitions, ownership models, stewardship workflows, and lifecycle management.
Ensure Business Glossary terms are mapped to physical data assets (tables, columns, streams, and semantic models) to bridge business and technical understanding across the organization.
Enable business friendly data discovery by integrating Purview Catalog, lineage views, and glossary context into analytics, Fabric workloads, and AI solutions.
Industry & Multi-Cloud Experience
Handson delivery ownership across industries including financial services, healthcare, manufacturing, retail/supply chain, energy, transportation, public sector, and media.
Solutioning, Pre-Sales & Technical Leadership
Frontier Engineering & Customer Enablement Skills
Strong troubleshooting and production support expertise, including performance, reliability, and security issues
Certifications (Preferred)
Two or more of the following:
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process.
