Staff Data Platform Engineer — AI-Driven Analytics

Intuit

Mountain View (CA)

On-site

USD 203,000 - 274,000

Full time

14 days+

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Job summary

Intuit’s Dev360 team seeks an experienced data platform engineer to architect scalable, fault-tolerant big-data platforms and enable data-driven decisions. You will work with Product, Engineering, and Central Data Lake teams to ensure extensibility, data governance, and efficient data sharing across units.

You will guide data normalization, lineage, ontology, and discoverability, while advancing AI-native analytics and datasets for actionable customer insights, driving CI/CD, testing, and

Qualifications

  • 8+ years in product analytics, web analytics or similar data analytics domains.
  • Proficiency in SQL and big data technologies; BI tool experience.
  • Strong Python/Java/Scala programming skills.
  • Experience with data pipelines, ETL/ELT and orchestration.
  • Familiarity with GenAI and AI-native analytics concepts.

Responsibilities

  • Architect, design, and build fault-tolerant, scalable big-data platforms.
  • Collaborate with Product, Engineering and Central Data Lake teams.
  • Develop scalable architectures for data normalization, governance, and lineage.
  • Work on AI-enabled analytics, Generative AI datasets, and ML-ready data.
  • Lead code reviews, CI/CD, testing, monitoring, and incident response.
  • Mentor junior engineers and promote engineering excellence.

Skills

SQL
Big data
Python/Java/Scala
Data pipelines
GenAI/AI-native

Education

Bachelor's degree in Engineering/Data Science/CS
Master’s degree preferred

Tools

Redshift
Spark
Hive
BigQuery
Tableau
Qlik
Dash

Job description

Intuit’s Dev360 team seeks an experienced data platform engineer to architect scalable, fault-tolerant big-data platforms and enable data-driven decisions. You will work with Product, Engineering, and Central Data Lake teams to ensure extensibility, data governance, and efficient data sharing across units.

You will guide data normalization, lineage, ontology, and discoverability, while advancing AI-native analytics and datasets for actionable customer insights, driving CI/CD, testing, and

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