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$170,000–$235,750.
Based on 239 similar postings.
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About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1117 open roles
on FindRole.
Listed pay typically runs
$186,160–$215,000
across 7 roles with salary data.
As a Senior Principal Architect, Data & Analytics Services within Corporate Technology – Corporate Data & Analytics Services, you will own the target-state architecture for platforms spanning Reference Data, KYC, and Common Trade and Position Data. You will drive modernization roadmaps, manage architectural governance, and oversee technical debt reduction while ensuring compliance with data risk management and resiliency standards. Your daily work involves establishing AI-enabled engineering patterns, mentoring architects, and serving as a primary technical interface for senior leadership to influence investment decisions. You will utilize expertise in data mesh, lakehouse, domain-driven design, and event-driven architectures alongside technologies like AWS, Kafka, Databricks, Spark, and Snowflake. The role addresses the challenge of managing large-scale, mission-critical data platforms within a highly regulated financial services environment, focusing on scalability, security, and the integration of generative AI into architectural workflows.
What does a Architect earn?
Median $235750 from 31 postings across 17 companies.
Own and maintain target-state architectures for Reference Data, KYC, and Common Trade and Position Data platforms.
Lead architecture governance by establishing design principles, guardrails, and review processes across the tower.
Drive modernization roadmaps to reduce technical debt while improving platform resilience, scalability, and cost efficiency.
Represent the tower in firmwide Architecture Review Boards and provide guidance on reference patterns.
Act as a primary technical advisor to senior leaders and stakeholders to influence technology investment decisions.
Provide hands-on oversight and coaching to domain architects and engineering leads on complex design challenges.
Ensure all platforms comply with data governance, risk management policies, and multi-region resiliency standards.
Establish AI-enabled engineering patterns and guardrails for agentic workflows across the software development lifecycle.
What we're looking for
Formal training or certification in architecture and software engineering concepts.
10+ years of applied experience including 7+ years leading architecture for large-scale, mission-critical data platforms in regulated environments.
Deep expertise in data architecture patterns such as data mesh, lakehouse, canonical modeling, domain-driven design, event-driven architectures, and API-led connectivity.
Strong knowledge of AWS, cloud-native platforms, container orchestration, CI/CD, IaC, observability, and platform engineering practices.
Experience with real-time and batch data processing technologies like Kafka, Databricks, Spark, or Snowflake.
Hands-on expertise in data governance including metadata management, lineage, quality, classification, and localization controls.
Experience shaping AI/Generative AI strategy, LLM integration, MLOps, and governing AI-enabled architectural patterns with security controls.
Experience in global financial services and regulated environments (preferred); relevant certifications like AWS Solutions Architect Professional, TOGAF, or CISSP (preferred).
Microsoft Fabric
Azure
Power BI
Microsoft Purview
Copilot Studio
Microsoft Foundry
AI
Data Engineering
Data Visualization
Data Governance
DORA
DevOps
SOW
GitHub
Python
SQL
AWS
Azure
Apache Spark
Apache Kafka
Data Warehousing
Data Lake
Lakehouse
MLOps
ETL
ELT
Scala
Java
Data Mesh
Medallion Architecture
Big Data
Agile Methodology
GenAI