Infosys - Senior Data Engineer

Responsibilities :

Enterprise Data Office is looking for Senior Data Engineers with a strong track record in building high-performing data and analytical solutions that transform, integrate, and meet diverse business data needs. You will play a key role in designing and developing modern data pipelines and platforms, supporting both traditional analytics and emerging AI/ML and Generative AI use cases.

You will be responsible for building data products, contributing across architecture, design, build, test, and deployment phases, and serving as a core member of an Agile team driving user story analysis and delivery.

**The Senior Data Engineer will be responsible for :

• Contributing to the design and implementation of data integration architecture and scalable data solutions on cloud-based platforms.

• Conducting source system analysis, data profiling, and data quality assessments to ensure accuracy and reliability of enterprise data.

• Building robust and scalable data pipelines (batch and real-time) to collect, process, and compute metrics from multiple financial data sources.

• Building scalable AI platforms to enable downstream use cases such as machine learning, predictive analytics, and Generative AI applications.

• Partnering with Data Science and AI/ML teams to support the development and deployment of Agentic AI systemsautonomous agents capable of decision-making, orchestration, and workflow execution.

• Designing and implementing Agents built using, and not limited to, Large Language Model integration, vector databases, embeddings, and retrieval-augmented generation (RAG) architectures.

• Assisting in the implementation of retrieval-augmented pipelines (RAG) by structuring and preparing enterprise data for semantic search and contextual retrieval.

• Contributing to data mapping and transformation design, ensuring alignment with models defined by Data Architects.

• Designing application architecture and articulating technical solutions for data pipelines to team members and stakeholders.

• Executing unit testing and validation of data outputs, ensuring high quality and adherence to data standards.

• Collaborating with business users during User Acceptance Testing (UAT) and supporting deployment into production environments.

• Ensuring adherence to change management, compliance, and regulatory requirements, particularly within financial services environments.

• Performing performance tuning, optimization, and code reviews to improve efficiency and reliability of data pipelines.

Required Qualifications :