As an Associate Vice President, Data Engineering at Deloitte Consulting, you will play the role of strategic architect who creates and(or) reviews enterprise grade architectures and also provides best practices for technical delivery for complex, enterprise-solutions. You will lead and guide multidisciplinary, global teams and serve as a senior mentor to managers and junior staff. You will partner closely with clients and internal stakeholders to align solution strategies with business goals, contribute to sales and proposal development, and ensure rigorous management of end-to-end project delivery, including scoping, estimation, and executive reporting for successful project outcomes.
Work you'll do
As an Associate Vice President, Data Engineering on the AI & Data team, you will be responsible for driving enterprise data engineering and AI architecture strategies that support complex transformation programs.
Shape enterprise data engineering, artificial intelligence, and generative artificial intelligence solution strategies aligned to client business objectives
Create and review enterprise architectures spanning data platforms, cloud infrastructure, security, application integration, and generative AI components
Lead multidisciplinary delivery teams across architecture, data engineering, machine learning engineering, and solution development to execute end-to-end programs
Guide technical delivery through architecture governance, estimation, risk management, and executive status reporting to support quality and delivery outcomes
Support business development through proposal contributions, solution design input, and executive-level client discussions on transformation roadmaps
The team
AI & Data offers a full spectrum of solutions for designing, developing, and operating cutting-edge Data and AI platforms, products, insights, and services. Our offering helps clients innovate, and enhance their data, AI, and analytics capabilities, ensuring they can mature and scale effectively.
AI & Data professionals will work with our clients to:
Design and modernize large-scale data and analytics platforms including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud, edge and AI/ML technologies, platforms and methodologies for storage, processing
Leverage automation, cognitive and AI based solutions to manage data, predict scenarios and prescribe actions
Drive operational efficiency by managing and upgrading their data ecosystems and application platforms, utilizing analytics expertise and providing As-a-Service models to ensure continuous insights and enhancements.
Location:
Bengaluru / Hyderabad / Pune / Chennai / Kolkata
Shift Timings:
As per Business need
Qualifications
Required:
18+ years of experience in data engineering, generative artificial intelligence, deep learning, or natural language processing, and BE, BTech, MCA, MSc (Computer Science), PhD, or MTech from an accredited university
Experience leading 30–40 member teams on end-to-end artificial intelligence or generative artificial intelligence transformation programs
Experience defining enterprise artificial intelligence strategy and designing enterprise architectures across data, generative artificial intelligence, security, and microservices-based environments
Experience building solutions using Python, Structured Query Language (SQL), TensorFlow, PyTorch, and cloud platforms including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP)
Experience with large language model optimization techniques including low-rank adaptation (LoRA), quantized low-rank adaptation (QLoRA), quantization, transformer architectures, and prompt engineering
Experience with machine learning operations (MLOps), retrieval-augmented generation (RAG), agentic AI frameworks, LangChain, LlamaIndex, and vector databases including Pinecone, Weaviate, or Chroma
Ability to travel 30-40%, on average, based on the work you do and the clients and industries/sectors you serve.
Preferred:
AI or cloud certifications such as AWS Certified Machine Learning - Specialty, Azure AI Engineer, or Google Cloud Professional Machine Learning Engineer
Experience with enterprise architecture frameworks and artificial intelligence governance practices
Experience publishing research, filing patents, or presenting thought leadership on generative artificial intelligence or agentic artificial intelligence topics
Experience mentoring senior engineering, architecture, or artificial intelligence teams across large-scale programs
