Pay: Salary not listed in the saved posting
Work setup: Unconfirmed
Employment: Unconfirmed

What you’ll work on

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).

Build scalable, high-performance data pipelines and analytics frameworks supporting enterprise data products.
Ensure the confidentiality and integrity of the information being accessed;
Drive implementation of multi-cloud architecture leveraging AWS and Azure (Azure Databricks, ADLS Gen2).

From the employer’s posting

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.

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

Tools in this posting

AWS
Azure
Databricks
Delta
S3
Snowflake
Iceberg

Source

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

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.

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

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

Job description

View original posting ↗

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

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.