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
Staff Software Data Engineer at Intuit on the QuickBooks Capital and Lending team, based in Mountain View, CA (onsite). You will help build enterprise-scale data engineering pipelines and features using modern data technologies, with substantial hands-on development and production support through quarterly on-call rotations.
What you’ll get to work on
Join an innovative engineering group focused on delivering reliable data capabilities for QuickBooks Capital customers. The role is centered on building and evolving production systems using Python, PySpark, Spark, SQL, DataBricks, AWS, Elastic Search, and Kafka, with a strong emphasis on engineering and operational excellence.
Responsibilities
- Review functional requirements and translate them into technical designs and specifications, then code and test the resulting solutions.
- Size work spanning medium to large complexity and manage timelines and deliveries.
- Design and develop software using data engineering technologies to support enterprise data workflows.
- Spend approximately 90% hands-on time designing, coding, testing, and supporting production systems through on-call coverage.
- Resolve defects during testing, pre-production, production, and subsequent post-release patches.
- Partner cross-functionally with product management, other engineering teams, and business units to drive forward results.
- Apply Agile Development practices, with experience in SCRUM or Extreme Programming methodologies.
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 a large existing codebase.
- Experience across the entire SDLC (Software Development Life Cycle).
- Proven experience building and supporting large-scale enterprise data engineering pipelines and featurization.
- Demonstrated passion for Engineering and Operational Excellence, including supporting production systems via quarterly on-call rotations to monitor systems and address production errors and incidents.
- Demonstrated ability to explain complex technical issues 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).
Compensation
USD 202,500 - 274,000 per year.
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