Lead Data Engineer (Data Platforms)

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




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