Join Microsoft Industry Solutions' Global Center for Innovation and Delivery (GCID) as a Data & AI Consultant. This role offers a unique opportunity to leverage your passion for technology and consulting expertise within end-to-end solution delivery. As part of a large, innovative organization, you'll contribute to high-profile data and AI projects, ensuring maximum customer value. We seek individuals with broad technical understanding, leadership potential, and a drive to deliver impactful solutions.

As a consultant, you will harness your technical acumen, leadership qualities, and creativity to craft and implement outstanding solutions. You will be instrumental in helping clients maximize the benefits derived from our cutting-edge technologies and services. Your role will involve close collaboration with architectural teams, customers, and partners, applying deep technical and business insights to accelerate the adoption of Microsoft solutions and align with client objectives.

Key responsibilities include acting as an individual contributor and integral member of the Data and AI team, ensuring timely and accurate delivery of assigned tasks. You will analyze business objectives and apply technical expertise to develop tailored solutions. A core focus will be accelerating client value through the design, development, and deployment of solutions on Microsoft technologies.

You will enhance project quality and team efficacy within engagements, proactively identifying and managing risks and dependencies beyond immediate scope. This includes developing contingency plans and mitigation strategies. Further, you will drive the adoption of cloud and Microsoft technologies, collaborating with sales and account teams to articulate value propositions and scale business with strategic customers.

Align with digital transformation initiatives, ensure the effective use of intellectual property, and contribute to the implementation of technology strategies with support from senior colleagues. You will also uphold information compliance and assurance policies, fostering stakeholder confidence and driving innovation across the organization to improve quality, productivity, and responsiveness.

We are seeking candidates with 4-6 years of relevant experience. A Bachelor's degree in Computer Science Engineering or equivalent work experience is required; higher relevant education is preferred.

Essential qualifications include a strong understanding of solution design, planning, development, and deployment of complex solutions. Experience in Data Engineering across cloud, on-premises, and hybrid environments is crucial, alongside foundational experience with Azure Data Services and data platform modernization. Proficiency in data warehousing and analytics platforms like Microsoft Fabric and Azure Synapse Analytics is expected, with Azure Databricks being a plus.

Candidates should have hands-on experience with AI-powered data pipelines using ETL/ELT tools such as Azure Data Factory, SSIS, Talend, Informatica, or Airflow. Exposure to data migrations, platform upgrades, and modernization efforts is important. A solid grasp of Big Data ecosystems (Spark, Databricks, Kafka, Hadoop) and AI/ML foundations, including building ML-ready datasets, feature engineering, and MLOps on Azure, is required.

Familiarity with Large Language Models (LLMs), model training/evaluation/deployment workflows, and Azure cloud AI stack (Azure OpenAI) is also necessary. Experience in NLP, Document Intelligence, Computer Vision, RAG frameworks, or AI Search is beneficial. Basic understanding of Prompt Engineering and exposure to deep learning/Gen AI frameworks like TensorFlow/PyTorch, along with orchestration frameworks like LangChain/LangGraph, is expected. Candidates should also be familiar with Responsible AI principles.

Experience working in Agile teams with Azure DevOps and understanding of DataOps and MLOps practices, automated testing, and CI/CD pipelines is key. Hands-on programming experience, preferably in Python, is essential. A consulting mindset, strong communication skills to articulate technical concepts to business stakeholders, comfort with ambiguity, and a desire for continuous learning and technical certifications are highly valued.