Fintech Principal Data Engineer

Intuit; Mountain View (CA); On-site; USD 245,000 - 332,000; Full time

Job summary

Intuit is seeking a Fintech Principal Data Engineer to bridge data needs between product teams and business consumers, owning cross-domain data products and a scalable data estate. You will shape canonical domain data and advance data ontology to support AI-ready analytics and compliant, auditable data lineage.

The role emphasizes collaboration with Fintech product teams, data stewards, and analytics, leveraging modern data-serving technologies and a SOX-compliant data platform to enable a

Qualifications

• 10+ years in data engineering or data architecture.
• Strong data modeling for transactional and analytical consumption; establish a source of truth across producers.
• Experience operating in regulated environments — SOX or equivalent controls.
• Demonstrated influence across product, analytics, risk, and compliance stakeholders.
• Communicates precisely with engineers and clearly with executives.
• Nice to have fintech/payments domain experience or knowledge graphs.

Responsibilities

• Understand how data is produced by product microservices; suggest and contribute application changes (event design, correlation IDs, data contracts)
• Canonical data modeling for Fintech domain data — profile and transactional entities, cross-domain concepts, and the certified model that serves as the single source of truth
• Understand how AI agents consume data and ontology concepts; contribute to the Fintech data ontology so agents reason over stated business meaning rather than inferring it from raw schemas
• Understand and solve for select use-case-specific needs of data consumers in areas like finance, compliance, marketing, and risk — including owning semantic views for consumers without their own engineering
• Build self-serve mechanisms and paved paths: contract tooling, certification infrastructure, and standards that let domain teams produce and publish quality data without a central bottleneck
• Design and build durable cross-domain data products consumed by multiple teams
• Evaluate and adopt modern data-serving technology (HTAP, online-OLAP, on-read materialization) to replace pipeline-heavy architectures — with SOX-grade consistency and lineage by construction
• Partner with data stewards across Fintech domains: drive standards adoption, review models, and steward changes so producers see their consumers before a change ships
• Balance tactical delivery with strategic build-out — and know when each takes priority
• Understanding of Intuit products (QBO and TT) and how Fintech offerings connect to them

Skills

Data modeling

Canonical modeling

Distributed systems

SQL mastery

SOX compliance

Influence without authority

Clear communication

Fintech domain

Python/Java

Tools

Kafka

Lakehouse

CDC

ETL tools

SQL

Job description

Overview

The Fintech Principal Data Engineer bridges data needs between data producers (Fintech product teams) and data consumers spanning compliance, finance, analytics, risk, and marketing. The role sits on the central Fintech Data team and carries both sides of its charter: keeping today's data estate delivering while building the target state — certified, canonically modeled domain data published once and consumed everywhere, served on a modern unified store, and made AI-ready through a financial-domain ontology.

Overview

The Fintech Principal Data Engineer bridges data needs between data producers (Fintech product teams) and data consumers spanning compliance, finance, analytics, risk, and marketing. The role sits on the central Fintech Data team and carries both sides of its charter: keeping today's data estate delivering while building the target state — certified, canonically modeled domain data published once and consumed everywhere, served on a modern unified store, and made AI-ready through a financial-domain ontology.

Responsibilities

• Understand how data is produced by product microservices; suggest and contribute application changes (event design, correlation IDs, data contracts)
• Canonical data modeling for Fintech domain data — profile and transactional entities, cross-domain concepts, and the certified model that serves as the single source of truth
• Understand how AI agents consume data and ontology concepts; contribute to the Fintech data ontology so agents reason over stated business meaning rather than inferring it from raw schemas
• Understand and solve for select use-case-specific needs of data consumers in areas like finance, compliance, marketing, and risk — including owning semantic views for consumers without their own engineering
• Build self-serve mechanisms and paved paths: contract tooling, certification infrastructure, and standards that let domain teams produce and publish quality data without a central bottleneck
• Design and build durable cross-domain data products consumed by multiple teams
• Evaluate and adopt modern data-serving technology (HTAP, online-OLAP, on-read materialization) to replace pipeline-heavy architectures — with SOX-grade consistency and lineage by construction
• Partner with data stewards across Fintech domains: drive standards adoption, review models, and steward changes so producers see their consumers before a change ships
• Balance tactical delivery with strategic build-out — and know when each takes priority
• Understanding of Intuit products (QBO and TT) and how Fintech offerings connect to them

Qualifications

• 10+ years in data engineering or data architecture, with hands‑on ownership of large‑scale production data systems
• Deep data modeling skill: canonical/domain modeling, schema design for both transactional and analytical consumption, and experience establishing a source of truth across many producers
• Strong distributed‑systems foundations: event streaming (Kafka), CDC, microservice data patterns, and modern stores (HTAP, online‑OLAP, lakehouse); SQL mastery
• Experience operating in regulated environments — SOX or equivalent controls, data lineage, auditability
• Demonstrated influence without authority: setting standards other teams adopt, working across product, analytics, risk, and compliance stakeholders
• Communicates at both altitudes — precise with engineers, crisp with executives
• Nice to have: fintech/payments domain experience; knowledge graphs or ontologies (FIBO or similar); experience enabling AI/agentic data consumption; Python/Java

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs.

Pay offered is based on factors such as job‑related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

The Expected Base Pay Range For This Position Is

Mountain View $245,000 - $331,500