Data Architect
- Sibitalent Corp
1 Days Ago
NA
C2C
Purchase-NY
8-10 Years
Required Skills: Databricks, Snowflake, Delta Lake, Apache Spark, Kafka, Flink, NiFi, Cloud, AWS, Azure, GCP, Architecture, Data Mesh, Data-as-a-Product, Federated data ownership, Self-service analytics, Cloud-native architectures, Distributed data systems
Job Description
The successful candidate will establish the architectural vision for modernizing data platforms across hybrid cloud and on-premises environments, supporting both high-volume batch processing and low-latency, real-time workloads.
This position combines deep hands-on technical expertise with enterprise influence, driving architectural decisions that maximize the value of Client data assets while meeting the highest standards for security, resiliency, compliance, and operational excellence.
Role:
• Serve as the senior technical leader for enterprise data architecture, partnering closely with the VP and senior technology leadership.
• Act as a trusted advisor to executive stakeholders, translating business strategy into scalable, secure, and resilient data architecture decisions.
• Define and evolve Mastercard's global data architecture strategy across hybrid cloud and on-premises environments.
• Architect secure, resilient solutions that meet global regulatory and compliance mandates, including GDPR, ISO 20022, and regional data localization requirements.
• Champion Data Mesh principles, enabling data-as-a-product capabilities, federated ownership, governance, and self-service access.
• Establish and drive enterprise architecture standards, design patterns, and engineering best practices through the Data & Analytics Architecture Review Board.
• Lead the modernization of legacy data platforms to cloud native architectures across AWS, Azure, and GCP.
• Drive adoption of modern data technologies, including Databricks, Snowflake, Delta Lake, and streaming platforms.
• Enable both real time and batch analytics use cases to support high availability, mission critical workloads.
• Evaluate and incorporate emerging technologies, including AI-enabled data platforms and agent-based architectures.
• Mentor and influence global engineering teams, fostering a culture of technical excellence, accountability, and thoughtful risk taking.
All About You:
• 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.
• Strong hands-on experience with technologies such as 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 for emerging use cases, including agentic commerce.
• 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, partnering effectively with product, engineering, and business stakeholders.
• Demonstrated ability to influence technical and business decisions at all levels, including C-suite stakeholders.
• Strong executive presence with the ability to translate complex architecture concepts into business language.
• Exceptional communication skills, with the ability to articulate complex technical concepts to executive and non-technical audiences.
• Strong Decency Quotient (DQ) with a track record of building inclusive, collaborative, high performing teams.
• Bachelor’s or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience.
This position combines deep hands-on technical expertise with enterprise influence, driving architectural decisions that maximize the value of Client data assets while meeting the highest standards for security, resiliency, compliance, and operational excellence.
Role:
• Serve as the senior technical leader for enterprise data architecture, partnering closely with the VP and senior technology leadership.
• Act as a trusted advisor to executive stakeholders, translating business strategy into scalable, secure, and resilient data architecture decisions.
• Define and evolve Mastercard's global data architecture strategy across hybrid cloud and on-premises environments.
• Architect secure, resilient solutions that meet global regulatory and compliance mandates, including GDPR, ISO 20022, and regional data localization requirements.
• Champion Data Mesh principles, enabling data-as-a-product capabilities, federated ownership, governance, and self-service access.
• Establish and drive enterprise architecture standards, design patterns, and engineering best practices through the Data & Analytics Architecture Review Board.
• Lead the modernization of legacy data platforms to cloud native architectures across AWS, Azure, and GCP.
• Drive adoption of modern data technologies, including Databricks, Snowflake, Delta Lake, and streaming platforms.
• Enable both real time and batch analytics use cases to support high availability, mission critical workloads.
• Evaluate and incorporate emerging technologies, including AI-enabled data platforms and agent-based architectures.
• Mentor and influence global engineering teams, fostering a culture of technical excellence, accountability, and thoughtful risk taking.
All About You:
• 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.
• Strong hands-on experience with technologies such as 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 for emerging use cases, including agentic commerce.
• 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, partnering effectively with product, engineering, and business stakeholders.
• Demonstrated ability to influence technical and business decisions at all levels, including C-suite stakeholders.
• Strong executive presence with the ability to translate complex architecture concepts into business language.
• Exceptional communication skills, with the ability to articulate complex technical concepts to executive and non-technical audiences.
• Strong Decency Quotient (DQ) with a track record of building inclusive, collaborative, high performing teams.
• Bachelor’s or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience.
