This role pays more than
97%
of similar roles. Most pay
$132,141–$215,125
— the shaded band above.
At the midpoint, this role pays about
$288k
versus about
$174k
for comparable roles.
Based on 240 similar postings.
Employer
About Intuit
Intuit is a financial software company known for products like TurboTax, QuickBooks, Mint, and Credit Karma, helping consumers and small businesses manage their finances and taxes. Industry: Financial Software & Technology
Intuit currently has
203 open roles
on FindRole.
Listed pay typically runs
$202,500–$274,000
across 180 roles with salary data.
Fintech Principal Data Engineer joins the central Fintech Data team to bridge data needs between product teams and consumers in compliance, finance, analytics, risk, and marketing. This role involves translating business requirements into scalable architecture by managing source microservices, event streams, and canonical modeling for profile and transactional entities. You will build a certified, canonically modeled domain data estate that is AI-ready through a financial-domain ontology while creating self-serve mechanisms like contract tooling and certification infrastructure. The work focuses on solving complex problems in the fintech space, including ensuring SOX-grade consistency and lineage. Key technical requirements include expertise in SQL, Kafka, CDC, microservice patterns, HTAP, online-OLAP, and lakehouse architectures. You will also utilize Python or Java while managing data stewardship and developing durable cross-domain products to replace pipeline-heavy architectures with modern serving technologies.
Translate business requirements into scalable data architecture by analyzing product microservices and consumer needs.
Develop canonical data models to create a single source of truth for fintech domain entities.
Contribute to the fintech data ontology to ensure AI agents can reason over business meanings.
Build self-serve infrastructure, contract tooling, and standards to enable teams to publish quality data independently.
Design and build durable cross-domain data products consumed by multiple internal teams.
Implement modern data-serving technologies like HTAP and online-OLAP while maintaining SOX-grade consistency.
Partner with data stewards to drive standard adoption and review model changes across fintech domains.
What we're looking for
10+ years of experience in data engineering or data architecture with hands-on ownership of large-scale production data systems.
Deep expertise in canonical and domain modeling, schema design for transactional/analytical use, and establishing a single source of truth.
Strong distributed systems foundations including Kafka, CDC, microservice patterns, modern stores (HTAP, online-OLAP, lakehouse), and SQL mastery.
Experience operating in regulated environments with SOX or equivalent controls, data lineage, and auditability.
Demonstrated ability to influence without authority by setting standards and collaborating across product, analytics, risk, and compliance stakeholders.
Ability to communicate effectively with both technical engineers and executive leadership.
Fintech/payments domain experience (preferred).
Knowledge of knowledge graphs or ontologies, AI/agentic data consumption, and Python/Java (preferred).
AI
React
Angular
SwiftUI
Kotlin
Java
TypeScript
Spring
Express
NodeJS
AWS
GCP
Distributed Systems
Full-stack Development
Scalability
Security
Observability
High Availability