Microsoft Industry Solutions - Global Center for 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 2000+ exceptional people, GCID presents a great opportunity for highly skilled services professionals to make a foray into consulting, solution development and delivery roles. The ideal consultant is passionate about technology, has breadth rather than specific product depth, and has the drive and courage to articulate and stand up for a great solution delivering true value for the client.
As a Data & AI consultant, you will deliver quality engagements with your expertise, as a key contributor to high profile data and AI projects to ensure customer value. The ideal candidate must have the ability to combine their technical skills, leadership skills, creativity, and customer focus to deliver great solutions to the customers and ensure they get the best out of our technologies and solutions. Consulting Delivery professionals bring subject matter and solution expertise to architectural teams, customers, and partners. They apply deep technical and business knowledge to accelerate the adoption of Microsoft devices and services by ensuring strategic, architectural, and operational alignment to customer and partner objectives.
Responsibilities
Works as an Individual contributor and key member of the Data and AI team and helps in timely execution of assigned deliverables with accurate estimates, work priorities, and accommodates project changes and trade-offs necessary for a successful release.
Applies technical experience and industry-specific knowledge to develop solutions, based on an analysis of how the proposed approach affects the business objectives of customers and partners.
Works to accelerate the value proposition of customer/partner engagements by helping to design, develop, and deploy solutions on Microsoft technologies and methodologies.
Contributes to the overall efficacy and quality of a project team’s technical delivery within assigned engagements.
Defines dependencies and risks that go beyond the immediate scope and timeframe for a complex project. Develops contingency plans, risk-mitigation implementation criteria, and alternative strategies to manage short- and long-term risks and manages technical escalations.
Drives opportunities to expand or accelerate the adoption and consumption of cloud and Microsoft technologies. Collaborates, as appropriate, with peers and other teams (e.g., Sales, account-aligned team) to scale the business with existing high-stake or strategic customers, by articulating/developing value propositions of strategic Microsoft products and services.
Align with innovation and digital transformation initiatives. Ensures the use of existing intellectual property (IP) and delivers value to customers.
Responsible for implementing the technology strategy with support from Senior peers
Applies information-compliance and assurance policies to ensure stakeholder confidence.
Drives new ways of thinking, across the division and subsidiary, to improve quality, engineering productivity, and responsiveness to feedback and changing priorities.
Consistently upskills through regular trainings and certifications on Azure Data and AI to be able to contribute to the future needs of the organization and customers
Qualifications
4 - 6 years of experience
Bachelor's degree in computer science engineering or equivalent work experience. Higher relevant education is preferred.
Knowledge of solution design, planning, development and deployment of complex solutions
One or more of the following certifications, or an equivalent industry certification is a plus: Microsoft Certified: Azure Data Engineer Associate (DP-600) / Microsoft Certified: Azure AI Engineer Associate (AI102) / Microsoft Certified: Azure Solution Architect Expert (AZ-305)
Core Data Engineering & Platform Skills
Hands-on experience in Data Engineering across cloud, on-prem, and hybrid environments
Strong foundational experience with Azure Data Services and data platform modernization initiatives
Handson exposure to Data Warehouse and analytics using platforms like Microsoft Fabric, and Azure Synapse Analytics; Azure Databricks is a plus
Experience/knowledge of one or more SQL and NoSQL database systems
Hands-on experience building AI-powered data pipelines using ETL/ELT tools like:
Azure Data Factory (ADF), SSIS, Talend, Informatica, Airflow
Exposure to data migrations, platform upgrades, and modernization efforts
Understanding of multitenant data platform designs, basic security hardening, and access control concepts
Knowledge of Big Data ecosystems like Spark, Databricks, Kafka, Hadoop, etc.
AI / ML Foundations
Experience building or supporting ML ready datasets and basic feature engineering
Exposure to operationalizing ML pipelines and MLOps concepts, on Azure stack
Foundational knowledge of:
Large Language Models (LLMs)
Model training, evaluation, and deployment workflows
Azure cloud and AI stack like Azure Foundry, Azure OpenAI, etc
Handson experience or knowledge in one or more of:
NLP, Document Intelligence & Indexing
Computer Vision
RAG frameworks or AI Search
Basic understanding of Prompt Engineering
Exposure to or knowledge of deep learning/Gen AI frameworks such as TensorFlow/PyTorch, and orchestration frameworks like LangChain/LangGraph
Familiarity with Responsible AI principles – fairness, interpretability, and governance
Engineering Practices & Delivery
Experience working in Agile teams with knowledge of/exposure to Azure DevOps
Understanding of DataOps and MLOps practices, automated testing, CI/CD pipelines, and deployment workflows, preferably on Azure Foundry
Knowledge of secure coding practices, observability basics, and performance considerations
Handson programming experience, preferably in Python
Consulting Mindset & Collaboration
Ability to work closely with senior consultants, architects, and customers to co-create innovative solutions with customers to help solve their business challenges
Strong communication skills to explain technical concepts to business stakeholders
Comfortable working in ambiguous environments, learning quickly, and adapting to change
Eagerness to build engineering excellence, reusable components, and best practices
Growth & Learning Orientation
Strong interest in continuous learning and technical certifications
Curiosity to explore emerging data and AI technologies
Willingness to receive feedback, grow technical depth, and expand ownership over time
Data Architecture Foundations (Good to have)
Good understanding of core data architecture patterns:
Dimensional modeling
Lambda and Kappa architectures
Timeseries data processing
Familiarity with Azure Stream Analytics and Azure Analysis Services
Awareness of data governance concepts and tools (opensource or proprietary)
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, read more about requesting accommodations.
Skills Required
- 4 - 6 years of experience
- Bachelor's degree in computer science engineering or equivalent
- Experience in solution design, planning, development and deployment of complex solutions
- Microsoft certifications (DP-600, AI-102, AZ-305) or equivalent industry certification
- Hands-on experience in Data Engineering across cloud, on-prem, and hybrid environments
- Strong foundational experience with Azure Data Services and data platform modernization
- Hands-on experience with Microsoft Fabric and Azure Synapse Analytics
- Experience with Azure Databricks
- Experience/knowledge of SQL and NoSQL database systems
- Hands-on ETL/ELT using Azure Data Factory (ADF), SSIS, Talend, Informatica, or Airflow
- Experience with data migrations, platform upgrades, and modernization efforts
- Understanding of multitenant data platform designs and basic security hardening/access control concepts
- Knowledge of Big Data ecosystems (Spark, Databricks, Kafka, Hadoop)
- Experience building ML-ready datasets and basic feature engineering
- Exposure to operationalizing ML pipelines and MLOps concepts on the Azure stack
- Foundational knowledge of LLMs, model training, evaluation, and deployment workflows (including Azure OpenAI)
- Hands-on experience or knowledge in NLP, Document Intelligence, Computer Vision, RAG frameworks, or AI Search
- Basic understanding of Prompt Engineering
- Familiarity with deep learning/Gen AI frameworks such as TensorFlow or PyTorch and orchestration frameworks like LangChain/LangGraph
- Familiarity with Responsible AI principles (fairness, interpretability, governance)
- Experience working in Agile teams and exposure to Azure DevOps
- Understanding of DataOps and MLOps practices, automated testing, CI/CD pipelines, and deployment workflows (preferably on Azure Foundry)
- Knowledge of secure coding practices, observability basics, and performance considerations
- Hands-on programming experience (preferably Python)
Microsoft Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.
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Fair & Transparent Compensation — Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
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Retirement Support — Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
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Parental & Family Support — Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.
Microsoft Insights
What We Do
At Microsoft, our mission is to empower every person and every organization on the planet to achieve more. Our mission is grounded in both the world in which we live and the future we strive to create. Today, we live in a mobile-first, cloud-first world, and the transformation we are driving across our businesses is designed to enable Microsoft and our customers to thrive in this world.
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