Staff Data Engineer - Capital & Lending Platform

Intuit; Lincoln (NE); On-site; USD 203,000 - 274,000; Full time

Job summary

Intuit is seeking a Staff Software Engineer in Data to join the QuickBooks Capital and Lending Platform. You’ll work on enterprise-scale data pipelines and features using Python, PySpark, Spark, SQL, DataBricks, AWS, Elasticsearch and Kafka.

You will spend most of your time coding, testing and supporting production systems while collaborating with product and other engineering teams. A strong data engineering background and 7+ years of experience are required.

Qualifications

• BS/MS in computer science or equivalent work experience.
• 7+ years’ experience developing data engineering pipelines using Python, PySpark, Spark, SQL, DataBricks, AWS, Elasticsearch, Kafka.
• 7+ years’ experience with BigData technologies.
• Extensive experience with Python and Spark.
• Proven ability to understand a large existing codebase.
• Experience with the SDLC.
• Experience building and supporting large scale enterprise data pipelines.

Responsibilities

• Understand requirements, design, code and test data engineering solutions.
• Size work of medium to large complexity and manage timelines.
• Design/develop software using data engineering technologies.
• Spend 90% on hands-on design, coding, testing and production support.
• Resolve defects across testing, pre-prod and production.
• Collaborate with product, engineering and business teams to drive results.
• Apply Agile SCRUM/XP methodologies.
• Model data, build data warehouses and ETL pipelines.
• Provide production support during on-call rotations.

Skills

Python

PySpark

Spark

SQL

DataBricks

AWS

Elasticsearch

Kafka

Education

BS/MS in Computer Science or equivalent

Tools

Python

Spark

Job description

Intuit is seeking a Staff Software Engineer in Data to join the QuickBooks Capital and Lending Platform. You’ll work on enterprise-scale data pipelines and features using Python, PySpark, Spark, SQL, DataBricks, AWS, Elasticsearch and Kafka.

You will spend most of your time coding, testing and supporting production systems while collaborating with product and other engineering teams. A strong data engineering background and 7+ years of experience are required.