Senior AI Data Engineer

MasterCard; Pune District; On-site; INR 2,500,000 - 3,800,000; Full time

Job summary

Mastercard is seeking a Senior AI Data Engineer to design, build, and optimize enterprise data platforms enabling scalable AI, machine learning, and Generative AI across the organization.

You will own production-grade data infrastructure supporting data ingestion, feature engineering, model training, inference, and continuous improvement, in collaboration with AI Engineers, Data Scientists, Platform Engineers and Solution Architects.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related field.

Responsibilities

• Design, build, and maintain scalable, cloud-native data platforms for enterprise AI applications.
• Lead batch and real-time data pipelines for AI model training, feature engineering, inference, and analytics.
• Develop data architectures supporting LLMs, embeddings, vector databases, and knowledge repositories.
• Create reusable data products, feature stores, metadata services, and data APIs.
• Ensure data quality with automated validation, profiling, lineage, observability, and monitoring.
• Optimize processing performance, cost, and reliability across distributed clouds.
• Collaborate with AI Engineers and Data Scientists for production datasets and model deployment.
• Impose data governance, security, privacy, and compliance controls per Mastercard standards.
• Design resilient, fault-tolerant pipelines with modern orchestration and event-driven architectures.
• Contribute to MLOps and AgenticOps capabilities delivering trusted data pipelines.

Skills

Python

SQL

Spark

Cloud-native

Airflow

AI/ML

Data governance

Stakeholder management

CI/CD

Communication

Education

Bachelor's or Master's in CS/Data Engineering/Info Systems

Tools

AWS

Azure

Google Cloud

Kafka/Kinesis/Azure Event Hubs

Airflow

Data Lakes/Lakehouse

Job description

Senior AI Data Engineer Overview

As a Senior AI Data Engineer within Mastercard's AI Center of Excellence, you will lead the design, development, and optimization of enterprise data platforms and pipelines that enable scalable AI, machine learning, and Generative AI solutions. You will be responsible for building production-grade data infrastructure that supports the complete AI lifecycle, including data ingestion, feature engineering, model training, inference, and continuous improvement Working closely with AI Engineers, Data Scientists, Platform Engineers, and Solution Architects, you will deliver secure, reliable, and high-performance data solutions while driving engineering best practices, data governance, and operational excellence across AI initiatives

Key Responsibilities

• Design, build, and maintain scalable, cloud-native data platforms that support enterprise AI and Agentic AI applications
• Lead the development of robust batch and real-time data pipelines for AI model training, feature engineering, inference, and analytics
• Build and optimize data architectures supporting LLMs, RAG, embeddings, vector databases, and AI knowledge repositories
• Develop reusable data products, feature stores, metadata services, and data APIs that accelerate AI solution development across the enterprise
• Ensure high standards of data quality through automated validation, profiling, lineage, observability, and monitoring
• Optimize data processing performance, scalability, reliability, and cost across distributed cloud environments
• Collaborate with AI Engineers and Data Scientists to prepare production-ready datasets and support model deployment, monitoring, and continuous improvement
• Implement data governance, security, privacy, and compliance controls that align with Mastercard's enterprise standards and regulatory requirements
• Design resilient, fault-tolerant data pipelines using modern orchestration, workflow automation, and event-driven architectures
• Contribute to the implementation of MLOps and AgenticOps capabilities by delivering trusted data pipelines that support automated AI workflows

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field
• Significant experience designing and implementing enterprise-scale data engineering solutions supporting AI and machine learning workloads
• Strong proficiency in Python, SQL, Spark, and distributed data processing frameworks
• Experience building cloud-native data platforms using AWS, Azure, or Google Cloud Platform
• Hands-on experience with data lakes, Lakehouse architectures, data warehouses, and object storage technologies
• Experience with streaming technologies such as Kafka, Kinesis, or Azure Event Hubs.
• Strong knowledge of workflow orchestration tools such as Apache Airflow, Azure Data Factory, or similar platforms
• Experience supporting AI and Generative AI solutions through feature engineering, vector databases, semantic search, embeddings, and RAG
• Solid understanding of data modeling, metadata management, data lineage, and enterprise data governance
• Experience implementing monitoring, observability, and operational support for production data pipelines
• Strong software engineering practices, including version control, automated testing, CI/CD, and Infrastructure as Code
• Excellent analytical, communication, and stakeholder management skills

What You'll Deliver

• Production-grade AI data platforms that enable secure, scalable, and high-performance AI and Generative AI solutions
• Trusted, high-quality data pipelines that accelerate AI model development, deployment, and operational excellence
• Reusable enterprise data capabilities that improve engineering productivity and support AI innovation across Mastercard
• Modern data engineering practices that ensure data quality, governance, security, and reliability while enabling the AI Center of Excellence to deliver enterprise-scale AI solutions

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• Abide by Mastercard's security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

Everyone wants easier ways to pay; we invent them. Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. Retailers want to fight fraud; we provide the tools.