Staff Data Engineer: Scale Data Platforms & Pipelines

Intuit, Inc.; Oakland (CA); Hybrid; USD 203,000 - 274,000; Full time

Benefits offered by this job

Cash bonus

Equity rewards

Benefits

Job summary

Intuit, Inc. invites a Staff Data Engineer to build scalable data and software solutions powering Credit Karma’s analytics and platforms.

You will work with Product, Data Scientists, and Engineers to design data warehouses, pipelines, and reusable frameworks, delivering reliable data processing at scale. Ideal candidates have 10+ years in software or data engineering, strong Python/Java/Scala skills, and deep SQL/data warehousing expertise.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field.
• 10+ years of software or data engineering experience.
• Strong programming in Python, Java, or Scala with solid fundamentals.
• SQL expertise and data warehousing concepts.
• Experience with large-scale data pipelines (Dataflow, BigQuery, Spark, Flink).
• Experience designing scalable data pipelines and distributed systems.
• Solid knowledge of SDLC and agile methodologies.
• Excellent communication and collaboration skills.

Responsibilities

• Design and develop scalable data and software systems across the data lifecycle.
• Build and maintain robust data pipelines (batch and streaming).
• Develop reusable datasets and data models for analytics and downstream systems.
• Contribute to platform and service development for data/experimentation.

Skills

Python

Java/Scala

SQL

Data warehousing

Airflow

Spark

BigQuery

Dataflow

Agile methods

Communication

Education

Bachelor's degree

Tools

Google Dataflow

BigQuery

Airflow/Composer

Spark

Flink

Job description

Intuit, Inc. invites a Staff Data Engineer to build scalable data and software solutions powering Credit Karma’s analytics and platforms.

You will work with Product, Data Scientists, and Engineers to design data warehouses, pipelines, and reusable frameworks, delivering reliable data processing at scale. Ideal candidates have 10+ years in software or data engineering, strong Python/Java/Scala skills, and deep SQL/data warehousing expertise.