Lead Data Engineer (Data Platforms)

Mastercard; Pune District; On-site; INR 5,000,000 - 8,000,000; Full time

Job summary

Mastercard seeks a Lead Data Engineer (Data Platforms) to design, build, and scale cloud-based data and analytics solutions across multi-cloud environments. The role emphasizes BI, data engineering, and platform capabilities using Databricks, Snowflake, AWS, and Azure, with a strong focus on governance and scalability.

The ideal candidate combines hands-on engineering expertise with leadership to mentor engineers and drive design decisions across the data platform ecosystem.

Qualifications

• 8+ years in software/data engineering or platform engineering.
• Hands-on with Databricks (AWS/Azure) and Snowflake.
• Experience building cloud data platforms, BI, and analytics.

Responsibilities

• Design and build cloud-native data/BI solutions on Databricks and Snowflake.
• Develop scalable data pipelines and analytics frameworks for data products.
• Lead multi-cloud architecture with AWS and Azure, including governance.
• Define CI/CD and IaC pipelines for data platform provisioning.

Skills

Databricks

Snowflake

AWS

CI/CD

Infrastructure as Code

Distributed systems

Leadership

Multi-cloud

Job description

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Lead Data Engineer (Data Platforms)

Role Summary

We are looking for a Lead Software Engineer to design, build, and scale cloud-based data and analytics solutions within Mastercard's Data Commercialization Platform (DCP). This role focuses on delivering Business Intelligence (BI), data engineering, and platform capabilities using Databricks, Snowflake, AWS, and Azure, while ensuring strong governance, scalability, and interoperability across multi-cloud environments. The ideal candidate will combine hands-on engineering expertise.

Key Responsibilities

Architecture & Development

• Design and develop cloud-native data and BI solutions using Databricks and Snowflake on AWS.
• Build scalable, high-performance data pipelines and analytics frameworks supporting enterprise data products.
• Drive implementation of multi-cloud architecture leveraging AWS and Azure (Azure Databricks, ADLS Gen2).

Platform Engineering & Integration

• Enable seamless integration across Databricks, Snowflake, AWS services, and Azure services.
• Build and maintain CI/CD pipelines, automation frameworks, and infrastructure-as-code for data platform provisioning.
• Implement secure and governed access patterns including RBAC, service principals, and enterprise identity integration.
• Support data platform interoperability across multiple compute engines and cloud providers.

Required Qualifications

• 8+ years of experience in software engineering / data engineering / platform engineering
• Strong hands-on experience with:
  Databricks (AWS / Azure)
• Snowflake
• AWS services (S3, Glue, EMR, IAM, etc.)
• Experience building cloud-based data platforms or BI/analytics solutions
• Strong knowledge of distributed systems, data processing, and scalable architectures
• Experience with CI/CD, Infrastructure as Code, and automation
• Proven ability to lead technical design and mentor engineers

Preferred Qualifications

• Experience with Azure (Azure Databricks, ADLS Gen2, AKS)
• Knowledge of open data formats (Delta Lake, Apache Iceberg)
• Experience with data governance frameworks and access control models
• Exposure to multi-cloud architecture and cross-platform interoperability
• Understanding of FinOps, cost optimization, and platform observability

Corporate Security Responsibility

• 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.