Staff Data Engineer — Big Data, Cloud & AI/ML

Intuit; San Diego (CA); On-site; USD 189,000 - 255,000; Full time

Job summary

Intuit's Consumer Group Data Engineering Team is seeking a Staff Software Engineer to lead data frameworks, ingestion pipelines, and tooling. You will be a technical leader across multiple scrum teams, applying advanced software engineering practices to design and support scalable data products.

Focus areas include Google Cloud, Spark, Flink, and AWS Big Data, with seniority guiding product direction and enabling rapid experimentation in collaboration with product managers and data scientists.

Qualifications

• Bachelor's or Master's degree in Computer Science or related field.
• 8+ years of software engineering with data engineering background.
• Expertise in Java/Spring, Scala for Spark streaming & Spark apps, or other JVM languages.
• 5+ years of SQL, XML, JSON, YAML, strong Python and Linux.
• Experience Building AI/ML and GenAI applications, growth-focused AI/ML.
• Experience with GenAI tech like Cursor or Windsurf to accelerate development.
• Cloud proficiency with AWS, GCP, or Azure; AWS emphasized.
• Data warehousing and analytics architecture for large data volumes.

Responsibilities

• 70–85% hands-on development across full software life cycle.
• Diagnose, fix bugs, troubleshoot and define ongoing solutions for cross-capability issues.
• Lead, estimate work for data initiatives; create technical design specifications and data models.
• Mentor engineers, raise team knowledge, and promote inclusive culture.

Skills

Java (Spring/Springboot)

Scala for Spark

Python

SQL

Big data architectures

Cloud platforms (AWS/GCP)

Education

BS or MS in Computer Science or related field

Tools

Docker

Spark

Kubernetes

Jupyter Notebook

Databricks

SageMaker

Job description

Intuit's Consumer Group Data Engineering Team is seeking a Staff Software Engineer to lead data frameworks, ingestion pipelines, and tooling. You will be a technical leader across multiple scrum teams, applying advanced software engineering practices to design and support scalable data products.

Focus areas include Google Cloud, Spark, Flink, and AWS Big Data, with seniority guiding product direction and enabling rapid experimentation in collaboration with product managers and data scientists.