Staff Data Engineer - QuickBooks Capital Mountain View, California
Intuit
Staff Data Engineer - QuickBooks Capital
Company Overview
Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.
Job Overview
The QuickBooks Capital Data team is responsible for building and maintaining the core data capabilities and pipelines that drive insights, decisions, and innovation for QuickBooks Capital. Our stakeholders include data scientists, backend engineers, product managers, and business leaders, all of whom rely on the team to deliver seamless data integrations, high-quality pipelines, and optimized data platforms. The data team plays a critical role in empowering QuickBooks Capital to scale, grow, and provide exceptional experiences to our customers.
As a Staff Data Engineer within the team, you will partner closely with cross-functional teams to execute on strategic data initiatives that shape the future of QuickBooks Capital’s data ecosystem. Tasks will include creating scalable data pipelines, designing data products, and optimizing data workflows to support analytics, business intelligence, and AI-driven use cases. The team prioritizes driving impactful outcomes using data, such as improving loan approval processes, enhancing customer insights, and fostering innovation through robust data infrastructure. If you are passionate about solving complex engineering problems, thrive in a collaborative environment, and have a pragmatic approach to building scalable and resilient data systems, this role could be a great fit for you.
Responsibilities
Execute and Deliver Scalable Data Solutions: Collaborate with external technical teams, data scientists, analysts, and stakeholders to understand requirements and translate business challenges into reliable data-driven solutions. Own the end-to-end execution of projects by designing, developing, and deploying data pipelines to meet the growing data needs of QuickBooks Capital.
Build and Optimize Data Platforms: Design, implement, and maintain robust data pipelines that transform and load large datasets across multiple domains. Focus on delivering data products with accuracy, reliability, and efficiency to empower actionable insights and data-driven decision-making.
Experiment and Innovate: Utilize tools like Databricks and advanced big data technologies to build and iterate on proof-of-concepts (POCs). Develop innovative solutions, including API integrations, advanced data modeling, and scalable platforms, to support analytics and machine learning use cases.
Create Business Impact with Data: Strategically apply data solutions to address key business challenges and deliver value through actionable insights. Uphold best practices in data governance and security while ensuring data accessibility, compliance, and reliability across the organization.
Collaborate and Empower the Team: Work effectively in a dynamic environment, collaborating with cross-functional teams to drive impactful results. Take ownership of monitoring pipeline performance, resolving issues, and mentoring team members to foster excellence and growth within the team.
Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
A minimum of 10 years of hands-on experience in data engineering or a similar role focused on big data platforms and solutions.
Strong understanding of data engineering and dimensional design fundamentals, front-end analysis / data visualization, and learning new technologies quickly. Good understanding of data federation techniques and aggregation of data at scale from multiple source systems.
Strong proficiency in programming languages such as Python, Java, or Scala, and experience with SQL.
Demonstrated experience with big data tools and frameworks such as Apache Spark, Hadoop or Databricks.
Experience with data modeling, data warehousing, and building ETL pipelines.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: $197,000 - $263,670