Job description
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.
