Staff Software Data Engineer
Big Data
Bigdata
Cloud Data Engineering
Cloud Data Platform
Cloud Operations
Cloud Platform
Cloud Platforms
Data Analysis
Data Analytics
Data Engineer
Data Engineering
Data Integration
Data Lakehouse
Data Pipeline
Data Pipelines
Data Platform
Data Processing
Data Warehouse
Database
Databases
Databricks
Elasticsearch
Engineer
Information Technology (IT)
Integration
Pyspark
Spark
SQL
Streaming Data
Job Description
Intuit is seeking a Staff Software Data Engineer for the QuickBooks Capital and Lending team in Mountain View, CA (onsite). In this role, you will design and deliver enterprise-scale data engineering pipelines and features, with substantial hands-on development and production support through on-call rotations.
Role Overview
You will join the QuickBooks Capital and Lending team to build data engineering pipelines and features for QuickBooks Capital customers. The work combines hands-on engineering with operational responsibilities to support production systems and address issues that arise after releases.
Responsibilities
- Review functional requirements, create technical designs and specifications, and implement with coding and testing.
- Size work for medium to large complexity and manage timelines and delivery.
- Design and develop software using data engineering technologies.
- Spend approximately 90% of time on designing, coding, testing, and supporting production systems, including on-call responsibilities.
- Identify and resolve defects or bugs during testing, pre-production, production, and post-release patching.
- Collaborate cross-functionally with product management, other engineering teams, and business units to drive outcomes.
- Apply Agile Development, SCRUM, or Extreme Programming practices as part of delivery.
Required Qualifications
- 7+ years developing data engineering pipelines using Python, PySpark, Spark, SQL, DataBricks, AWS, Elastic Search, and Kafka.
- 7+ years working on Big Data technologies.
- BS/MS in computer science or equivalent work experience.
- Strong experience with Python and Spark, including the ability to understand and work within a large existing codebase.
- Experience across the entire Software Development Life Cycle (SDLC).
- Demonstrated ability to build and support large-scale enterprise data engineering pipelines and data feature development.
- Demonstrated operational excellence and engineering focus, including production support via quarterly on-call rotations to monitor systems and resolve production errors and incidents.
- Demonstrated communication skills, including the ability to explain complex technical topics to both technical and non-technical audiences.
- Strong understanding of the software design and architecture process.
- Experience with unit testing and Test-Driven Development (TDD).
Key Technologies
- Python
- PySpark
- Spark
- SQL
- DataBricks
- AWS
- Elastic Search
- Kafka
Location and Compensation
Location: Mountain View, CA (onsite)
Salary Range: USD 202,500 to 274,000 per year
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