Staff Data Engineer

Intuit

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Mountain View, CASan Diego, CA
Salary
$202,500–$274,000 / yr
Posted
42 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $192k
This role $238k
$143k most similar roles pay here $288k

This role pays more than 84% of similar roles. Most pay $162,000–$221,000 — the shaded band above. At the midpoint, this role pays about $238k versus about $192k 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 174 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 152 roles with salary data.

Most-posted roles

View all roles at Intuit

At a glance

TL;DR · Staff Data Engineer

As a Staff Data Engineer - Dev360, you will join the Dev360 team to build and architect fault-tolerant, scalable big-data platforms that support high-velocity, high-volume data use cases. You will be responsible for designing architectures for data normalization, lineage, governance, and ontology while collaborating with product teams to curate datasets for advanced analytics, including Generative AI and Machine Learning. Your daily work involves overseeing data pipelines, performing code reviews, and establishing processes for unit testing, CI/CD, and monitoring. The role requires advanced proficiency in SQL, big data technologies like Redshift, Spark, Hive, or BigQuery, and BI tools such as Tableau, Qlik, or Dash. You must possess strong programming skills in Python or Java/Scala to solve complex problems regarding product performance tracking and software development lifecycle visibility across diverse systems.

What does a Data Engineer earn in California?

Median $199800 from 35 postings across 19 companies.

See salary data

What you'll do

  • Architect and build fault-tolerant, scalable big-data platforms for high-volume data use cases.
  • Develop architectures for data normalization, lineage, governance, and discoverability across diverse systems.
  • Curate and administer datasets required for advanced analytics, including Generative AI and Machine Learning.
  • Execute code reviews and establish processes for unit testing, CI/CD, and performance monitoring.
  • Design end-to-end data pipelines and workflow orchestration tools to support product analytics.
  • Translate business strategies into testable hypotheses and actionable learning agendas.
  • Mentor junior team members in technical proficiency and collaborative problem resolution.

What we're looking for

  • Bachelor's degree in Engineering, Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
  • Master's degree is preferred.
  • 8+ years of experience working with product analytics, web analytics, or similar data analytics domains.
  • Advanced proficiency in SQL, big data technologies (Redshift, Spark, Hive, BigQuery), and BI tools (Tableau, Qlik, Dash).
  • Strong programming skills in Python or Java/Scala.
  • Experience engineering data pipelines, workflow orchestration tools, and architecting end-to-end big data and analytical platforms.
  • Understanding of AI-native architectures and GenAI platforms to assess implications for data, testing, and behavior.
  • Strong data storytelling skills and the ability to communicate insights to influence leadership.

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