Principal Software Engineer, Data Architecture

Mastercard

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Quick summary

Work type: On-site
Location: Purchase, NYNew York, NY
Salary: $195,000–$323,000 / yr
Posted: 5 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $199k

This role $259k

$121k $345k

below market most similar roles pay here above market

This role pays more than 83% of similar roles. Most pay $171,650–$226,350 — the blue band above. At the midpoint, this role pays about $259k versus about $199k 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 150 open roles on FindRole.

Listed pay typically runs $122,000–$207,000 across 142 roles with salary data.

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View all roles at Mastercard

At a glance

TL;DR · Principal Software Engineer, Data Architecture

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The Principal Software Engineer, Data Architecture joins the Data & Analytics organization to serve as the senior technical authority for global enterprise data architecture. This role involves defining the architectural vision for modernizing data platforms across hybrid cloud and on-premises environments, supporting high-volume batch processing and low-latency, real-time workloads. Key responsibilities include establishing standards for security, resiliency, and compliance with mandates like GDPR and ISO 20022. The engineer will champion Data Mesh principles and lead the migration of legacy systems to cloud-native architectures. Required technical expertise includes Apache Spark, Kafka, Flink, NiFi, Databricks, Snowflake, and Delta Lake across AWS, Azure, and GCP. The role solves complex problems regarding data governance, federated ownership, and integrating AI-enabled data platforms into highly regulated global environments.

What does a Software Engineer earn in New York?

Median $215356 from 242 postings across 55 companies.

See salary data

Skills

Data Architecture AWS Azure GCP Databricks Snowflake Apache Spark Kafka Flink NiFi Delta Lake Data Mesh Agile SAFe Batch Processing

What you'll do

Define and evolve the global data architecture strategy across hybrid cloud and on-premises environments.
Architect secure, resilient 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 to cloud-native architectures on AWS, Azure, and GCP.
Drive the adoption of modern data technologies including Databricks, Snowflake, Delta Lake, and streaming platforms.
Establish enterprise architecture standards and design patterns through the Data & Analytics Architecture Review Board.
Evaluate and incorporate emerging technologies such as AI-enabled data platforms and agent-based architectures.
Mentor global engineering teams to foster a culture of technical excellence and accountability.

What we're looking for

Proven experience as a Principal Engineer, Lead Architect, or equivalent technical leadership role driving enterprise-scale data architecture.
Deep expertise designing, building, and operating distributed data systems at a global scale.
Strong hands-on experience with Apache Spark, Kafka, Flink, NiFi, Databricks, Snowflake, and modern cloud-native data 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 lead and influence architectural initiatives within Agile, SAFe, or product-centric delivery models.
Bachelor’s or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience.

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