Data Engineering Manager/Architect - Deloitte

Manager Data Engineering & AI | Financial Services Deloitte Touche Tohmatsu India LLP | Engineering, AI & Data Experience: 8 10 years Location: Pune Practice: Engineering, AI & Data Employment Type: Full-time About the Role We are looking for an experienced Data Engineering Manager to join Deloitte's Engineering, AI & Data practice, with a strong focus on Financial Services . The role will involve leading the design, development, modernization, and delivery of enterprise-scale data engineering and AI-enabled data solutions for financial services clients. The candidate will work closely with client technology and business stakeholders to define data strategies, architect modern data platforms, enable AI/ML and Generative AI use cases, lead engineering teams, and deliver scalable cloud-based solutions. The candidate should have strong expertise in Microsoft Azure data engineering and cloud technologies , with hands-on experience delivering data transformation initiatives within the Banking, Financial Services, Insurance (BFSI) sector. Exposure to building AI-ready data platforms, data foundations for AI/ML, and GenAI use cases will be an added advantage. Key Responsibilities Data Engineering, AI & Azure Architecture • Lead the design and implementation of scalable, secure, and high-performing Azure-based data platforms . • Architect and deliver modern data solutions leveraging Azure services across data ingestion, processing, storage, analytics, and orchestration. • Design and oversee batch and real-time/streaming data pipelines and ETL/ELT frameworks. • Define data models, data integration patterns, processing frameworks, and engineering standards. • Lead data platform modernization and migration initiatives from legacy/on-premises environments to Azure. • Design AI-ready data architectures and data foundations to support advanced analytics, AI/ML, and Generative AI use cases. • Work with AI/ML and GenAI teams to enable high-quality, governed, and accessible enterprise data for AI solutions. • Identify opportunities to leverage Azure AI services, machine learning platforms, vector databases, RAG architectures, and other AI capabilities within enterprise data environments. • Required Skills & Experience • 8 10 years of experience in Data Engineering, Data Platforms, Data Architecture, or Cloud Data Engineering. • Strong hands-on experience with Microsoft Azure data engineering technologies . • Strong experience with Azure Data Factory, ADLS, Azure Databricks and/or Azure Synapse . • Strong understanding of ETL/ELT, data modelling, data warehousing, data lakes, lakehouse architectures, and distributed data processing . • Experience designing and implementing enterprise-scale data pipelines. • Understanding of AI/ML and Generative AI concepts , with exposure to building data foundations or pipelines supporting AI/ML and GenAI solutions. • Exposure to AI-ready data architectures, vector databases, RAG pipelines, feature stores, or ML data pipelines is preferred. • Strong understanding of Azure security, IAM, networking, governance, monitoring, and cloud cost optimization . • Financial Services/BFSI domain experience required , preferably across Banking, Capital Markets, and Wealth Management. • Good to have experience with Google Cloud Platform (GCP) and services such as BigQuery, Dataflow, Dataproc, or equivalent. • Preferred Qualifications • Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science , or a related discipline. • Azure certifications such as Azure Data Engineer Associate (DP-203) or equivalent are preferred. • Exposure to Azure AI / Machine Learning, Azure OpenAI, Microsoft Fabric, or other enterprise AI technologies is an advantage. • Strong analytical, problem-solving, client-facing communication, consulting and stakeholder management skills.