Lead Data Engineer
Mastercard · Pune · 8+ yrs experience · Posted 2026-06-08
Tech stack: AWS, Azure
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About the role
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.
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.
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
- 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
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
- 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
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.