Principal Consultant - Data&AI
Microsoft
Principal Consultant - Data&AI
Multiple Locations, India
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Overview
Microsoft Industry Solution - Global Delivery Center (GDC) delivers end-to-end solutions by enabling accelerated adoption and productive use of Microsoft technologies. An organization of well over 1000+ exceptional people, GDC 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 GDC org, 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.
Qualifications
- 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations.
- Over 10 years of experience in designing and leading Data Warehouse, Lakehouse and analytical solutions using platforms such as Microsoft Fabric, Azure Synapse Analytics, Snowflake, and Teradata
- Strong Experience in large database solutions, on premises, cloud, and hybrid implementations
- Strong experience in Serverless Architecture/Microservices
- Strong experience of full application life cycle design tools and methodologies
- Strong experience in one or more technologies under each of the following
- Big Data stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight.
- Database Stack: Strong database experience with OLTP/OLAP, data storage mechanism and architecture,
- Columnar (RedShift, Vertica)
- OSS (MySQL, PostgreSQL and MariaDB)
- CosmosDB (MongoDB, Redis, Cassandra - key-value stores, graph databases, RDF triple stores)
- Level 400 knowledge in one (and preferably more) of the database engines, engine stack including engine level debugging for ex; CXPACKET analysis, Disk throttling, storage, IO contentions, Network contentions, performance optimizations.
- Strong experience in Data Engineering:
- Data Architecture: Dimensional Modelling, Lambda/Kappa architecture, Time series data
- Azure Stream Analytics, Azure Analysis ServiceMust have experience in two or more relational DBMS (Microsoft SQL, Azure Synapse and/or Oracle, Teradata, Netezza)
- Ability to design and drive large Data Migrations using necessary ETL technologies: ADF, SSIS, Talend, Pentaho, Informatica. Drive multi-tenant database designs, security hardening of the data platform.
- Expertise in implementation of Data governance practices using either open source or proprietary tools.
- Expertise in Data Ops
- Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible.
- Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain.
- Strong experience in AI/ML:
- Expertise in building and operationalizing ML pipelines, including feature engineering, model training, evaluation, and deployment (MLOps).
- Expertise in Azure ML and Open AI.
- Hands-on experience in Natural Language Processing, Document Intelligence & Indexing or Customer Vision or RAG Framework or AI Search
- Good understanding of Prompt Engineering Basics.
- Experience integrating AI models into enterprise data platforms and driving intelligent automation across business processes.
- Familiarity with Responsible AI principles, including fairness, interpretability, and governance of AI models.
Nice to have Skills
- Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalogue, Data Mesh and Data Modelling.
- Multi-cloud experience a plus - Azure, AWS, Google
Responsibilities
AI-First Delivery Leadership
- Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable.
- Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes.
- Drive engineering excellence through reusable components, accelerators, and scalable architecture.
- 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.
- Act as a technical point of contact for clients, translating business requirements into scalable technical solutions.
- Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes.
Engineering Excellence
- Champion high-quality engineering practices across all delivery engagements.
- Ensure adherence to coding standards, architectural integrity, and performance benchmarks.
- Promote secure coding, test-driven development, and observability as default practices.
- Encourage continuous learning and technical certifications to maintain cutting-edge expertise.
- Drive adoption of modern delivery methodologies (Agile, DevOps, CI/CD) to ensure robust and scalable solutions.
- Foster a culture of technical rigor, innovation, and accountability within the team.
Innovation & Thought Leadership
- Monitor and evaluate emerging technologies to inform strategic direction.
- Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact.
- Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement.
Client Engagement & Solutioning
- Engage with clients to understand business needs and provide expert guidance throughout the project lifecycle.
- Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals.
- Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery.
Team Management & Mentorship
- Lead and mentor cross-functional teams, fostering a culture of learning, collaboration, and technical excellence.
- Conduct reviews, provide feedback, and support professional development of team members.
Quality & Compliance
- Ensure all deliverables meet quality standards, security, and regulatory requirements.
- Promote secure coding, test-driven development, and observability as default practices.
Strategic Partnering
- Serve as a strategic partner for internal and external stakeholders on key initiatives.
- Provide strategic guidance and execution oversight to ensure alignment with organizational goals.
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