Back to jobs

Fintech Principal Data Engineer

Mountain View, California

This posting is no longer in the employer’s latest listings.

We’re checking whether it has closed. This saved copy remains available for reference.

Pay
$245,000–331,500/year · BaseAnnual period assumed — pay source
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 (see more about our compensation and benefits at Intuit®: Careers | Benefits). 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
Read the full posting
Work setup
Unconfirmed
Employment
Unconfirmed
Check the employer’s page ↗

What you’ll work on

Full posting
  • Design and build durable cross-domain data products consumed by multiple teams

  • Partner with data stewards across Fintech domains: drive standards adoption, review models, and steward changes so producers see their consumers before a change ships

From the employer’s posting
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
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

What you’ll bring

All qualifications

Core experience

  • 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
  • Experience operating in regulated environments — SOX or equivalent controls, data lineage, auditability
Qualification wording
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
Experience operating in regulated environments — SOX or equivalent controls, data lineage, auditability

Tools in this posting

  • SQL
  • Kafka
  • Python
  • Java
Source — Tool mentions in context
- 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
- 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 (see more about our compensation and benefits at Intuit®: Careers | Benefits). 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.

Job description

View original posting ↗

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.

This job includes understanding how product engineers operate, how the products work, and what data consumers need, in order to translate business requirements into data architecture that scales. You will work at every altitude: hands-on with source microservices and event streams, at the modeling table defining canonical domain entities, and at the whiteboard with senior leadership shaping how a multi-billion-dollar fintech business governs its data.


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 (see more about our compensation and benefits at Intuit®: Careers | Benefits). 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

Your next step

Check the employer’s posting for the current role and application details.

Already applied? Track this application

Source & posting history

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay
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 (see more about our compensation and benefits at Intuit®: Careers | Benefits). 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
Location & working pattern

Mountain View, California

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Status in our records
Unknown — awaiting fresh evidence
First seen by us
Sep 14, 2026
Recorded sightings
143
Last seen by us
Oct 6, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

Report an error

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.