This role pays more than
81%
of similar roles. Most pay
$184,628–$242,875
— the shaded band above.
At the midpoint, this role pays about
$259k
versus about
$214k
for comparable roles.
Based on 240 similar postings.
Employer
About Mastercard
Mastercard is a global technology company in the payments industry, processing transactions between financial institutions and merchants using its extensive network of credit, debit, and prepaid card products. Industry: Payments Technology & Financial Services
Mastercard currently has
128 open roles
on FindRole.
Listed pay typically runs
$122,000–$207,000
across 114 roles with salary data.
Principal Software Engineer, Data Architecture joins the Data & Analytics organization to serve as a senior technical authority defining global enterprise data architecture strategy. This role involves establishing architectural visions for modernizing data platforms across hybrid cloud and on-premises environments while supporting high-volume batch processing and low-latency, real-time workloads. The engineer will champion Data Mesh principles, advocate for data-as-a-product capabilities, and lead the modernization of legacy systems into cloud-native architectures. Key responsibilities include ensuring compliance with global regulations like GDPR and ISO 20022 while integrating AI-enabled platforms. The role requires expertise in Apache Spark, Kafka, Flink, NiFi, Databricks, Snowflake, and Delta Lake across AWS, Azure, and GCP environments. This position solves complex problems regarding data governance, security, and scalability within a highly regulated global ecosystem to ensure resilient, mission-critical data availability.
What does a Software Engineer earn in New York?
Median $216000 from 213 postings across 43 companies.
Define and evolve the global enterprise data architecture strategy across hybrid cloud and on-premises environments.
Architect secure, resilient data solutions that comply with global regulatory mandates like GDPR and ISO 20022.
Champion Data Mesh principles to enable data-as-a-product capabilities and federated ownership.
Lead the modernization of legacy data platforms into cloud-native architectures across AWS, Azure, and GCP.
Drive the adoption of modern technologies including Databricks, Snowflake, Delta Lake, and streaming platforms.
Integrate AI-enabled data platforms and agent-based architectures with appropriate governance and guardrails.
Establish enterprise architecture standards and design patterns through the Data & Analytics Architecture Review Board.
Mentor global engineering teams to foster a culture of technical excellence and accountability.
What we're looking for
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience.
Proven experience as a Principal Engineer, Lead Architect, or equivalent technical leadership role driving enterprise-scale data architecture and platform strategy.
Deep expertise designing, building, and operating distributed data systems at global scale.
Hands-on experience with technologies such as Apache Spark, Kafka, Flink, NiFi, Databricks, Snowflake, and modern cloud-native platforms.
Demonstrated success modernizing data platforms using cloud native architectures across AWS, Azure, and/or GCP.
Experience integrating AI driven capabilities into data platforms with appropriate governance and guardrails.
Strong understanding of data governance, security, and regulatory compliance in highly regulated, global environments.
Proven ability to influence technical and business decisions at all levels, including C-suite stakeholders.