Intuit Inc.
Principal Software Engineer - Data Engineering
Intuit Inc., Mountain View, California, us, 94039
Come join the Virtual Expert Platform Data Engineering Team as a Principal Software Engineer. Intuit is the global leader in financial management software where we have pioneered the shift to Virtual Platforms, cloud computing for consumers, small businesses and those that serve them. Intuit moves as fast as a startup, and we are constantly disrupting ourselves as we identify major new technology and design trends that are needed to deliver our mission to power prosperity around the world. Our groups are fast-paced teams focused on delivering innovative capabilities, and having fun while doing it.
The Virtual Expert Platform (VEP) powers TurboTax Live by providing the underlying services and capabilities that enable AI-driven tax expertise for customers. It acts as a foundational platform for critical Intuit offerings, ensuring rapid onboarding and customization to meet their unique requirements and scale.
As a Principal Software Engineer, you will define and drive the data strategy for the VEP team, providing technical leadership and using expertise in cloud platforms and big data technologies to solve complex data problems and align data infrastructure with strategic business goals. You will participate in the entire product lifecycle for data, software products, and services that are broad in scope and complexity, applying a full understanding of software engineering methodologies and industry best practices for data products. You will utilize specialized knowledge to design, develop, and maintain Intuit’s data solutions.
At Intuit, we are passionate about growing the careers of talented technologists who are equally passionate in solving the most complex customer problems. This leader is expected to innovate and enable applications that are highly interactive, fast and can scale to billions of interactions.
Responsibilities
Technical Leadership & Execution: Drive end-to-end data architecture in all phases of the software life cycle across Intuit’s product offerings Lead the technology evolution of high-volume data products, including data, analytics, productivity, and tools Collaborate with business stakeholders to understand their needs and translate them into effective, scalable solutions Growth & Product Mindset
Understand customer behavior, funnel metrics, and business levers, ensuring every technical investment drives measurable impact Demonstrate a deep understanding of current technology trends and best practices. Leverage expertise in end-to-end system design using a mindset of five pillars (Operational Excellence, Security, Reliability, Performance Efficiency, and Cost Optimization), creating and promoting standards and guiding teams to balance long and short outcomes Actively stay abreast of industry best practices, share learnings, experiment, and apply cutting-edge technologies while proactively identifying opportunities to enhance software applications with AI technology Introduce new approaches and techniques rooted in the latest industry trends and best practices that alter projects\' trajectories. Create reusable and self-serve libraries/tools and leverage Intuit technology Mentorship & Cross-Functional Collaboration
Raise team knowledge, skill, and engagement through collaborative technical sessions and other tech forums. Mentor and assess engineers, continuously developing and maintaining a strong talent pipeline, and actively participating in calibrations and assessments. Role model and develop a culture of inclusivity on the team. You will guide and mentor engineers to elevate experimentation and growth engineering capabilities across the organization Collaborate effectively with peer engineers, data scientists, analysts, and architects; proactively connect and collaborate with adjacent teams and cross-functional partners to ideate and solve problems together Influence and communicate effectively with non-technical audiences, including senior product and business management. You will explain complex technical architectures and designs to both technical and non-technical stakeholders and drive decisions Intuit provides a competitive compensation package with a strong pay-for-performance rewards approach. The expected base pay range for this position is: Bay Area California $254,500 - $344,000 Southern California $242,000 - $327,500 This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs. Qualifications
BS or MS in Computer Science, Data Engineering, or a related field 15+ years of software engineering experience, with a strong background in data engineering Expertise in developing data pipelines, big data frameworks like Apache Spark, Hadoop, and streaming technologies such as Kafka 5+ years of professional experience with SQL, XML, JSON, YAML, strong Python and Linux Knowledge of AI / ML, Generative AI, and experience with growth-focused AI/ML applications (personalization, recommendation engines, predictive modeling) Experience with GenAI technologies to accelerate development and build reusable GenAI platform components Experience with tools and frameworks such as Docker, Spark, Scala, Jupyter Notebook, Databricks Notebooks, Kubernetes, Feature Management Platforms, and SageMaker Knowledge of Agile, SCRUM, and/or Extreme Programming methodologies Strong cloud experience (AWS, Azure, or GCP) including AWS services (EC2, S3, EMR, DynamoDB, Athena) or equivalent Deep knowledge of data lake/warehouse solutions (Snowflake, Databricks, or similar) Understanding of metadata management, data lineage, and data governance principles 5+ years of experience with big data technologies (Hive, Hadoop, Kafka, columnar databases, graph databases) and stream processing or near real-time data ingestion Experience with low-latency NoSQL datastores (e.g., DynamoDB, HBase, Cassandra, MongoDB) is a plus; experience with stream processing (Spark Streaming, Flink) is a plus Excellent interpersonal and communication skills and ability to influence at all levels Strategic mindset with the ability to influence short- and long-term strategy for maximum business impact Ability to use data to influence product and technology decisions within their scope Ability to quickly understand new technical landscapes and drive immediate impact
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Technical Leadership & Execution: Drive end-to-end data architecture in all phases of the software life cycle across Intuit’s product offerings Lead the technology evolution of high-volume data products, including data, analytics, productivity, and tools Collaborate with business stakeholders to understand their needs and translate them into effective, scalable solutions Growth & Product Mindset
Understand customer behavior, funnel metrics, and business levers, ensuring every technical investment drives measurable impact Demonstrate a deep understanding of current technology trends and best practices. Leverage expertise in end-to-end system design using a mindset of five pillars (Operational Excellence, Security, Reliability, Performance Efficiency, and Cost Optimization), creating and promoting standards and guiding teams to balance long and short outcomes Actively stay abreast of industry best practices, share learnings, experiment, and apply cutting-edge technologies while proactively identifying opportunities to enhance software applications with AI technology Introduce new approaches and techniques rooted in the latest industry trends and best practices that alter projects\' trajectories. Create reusable and self-serve libraries/tools and leverage Intuit technology Mentorship & Cross-Functional Collaboration
Raise team knowledge, skill, and engagement through collaborative technical sessions and other tech forums. Mentor and assess engineers, continuously developing and maintaining a strong talent pipeline, and actively participating in calibrations and assessments. Role model and develop a culture of inclusivity on the team. You will guide and mentor engineers to elevate experimentation and growth engineering capabilities across the organization Collaborate effectively with peer engineers, data scientists, analysts, and architects; proactively connect and collaborate with adjacent teams and cross-functional partners to ideate and solve problems together Influence and communicate effectively with non-technical audiences, including senior product and business management. You will explain complex technical architectures and designs to both technical and non-technical stakeholders and drive decisions Intuit provides a competitive compensation package with a strong pay-for-performance rewards approach. The expected base pay range for this position is: Bay Area California $254,500 - $344,000 Southern California $242,000 - $327,500 This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs. Qualifications
BS or MS in Computer Science, Data Engineering, or a related field 15+ years of software engineering experience, with a strong background in data engineering Expertise in developing data pipelines, big data frameworks like Apache Spark, Hadoop, and streaming technologies such as Kafka 5+ years of professional experience with SQL, XML, JSON, YAML, strong Python and Linux Knowledge of AI / ML, Generative AI, and experience with growth-focused AI/ML applications (personalization, recommendation engines, predictive modeling) Experience with GenAI technologies to accelerate development and build reusable GenAI platform components Experience with tools and frameworks such as Docker, Spark, Scala, Jupyter Notebook, Databricks Notebooks, Kubernetes, Feature Management Platforms, and SageMaker Knowledge of Agile, SCRUM, and/or Extreme Programming methodologies Strong cloud experience (AWS, Azure, or GCP) including AWS services (EC2, S3, EMR, DynamoDB, Athena) or equivalent Deep knowledge of data lake/warehouse solutions (Snowflake, Databricks, or similar) Understanding of metadata management, data lineage, and data governance principles 5+ years of experience with big data technologies (Hive, Hadoop, Kafka, columnar databases, graph databases) and stream processing or near real-time data ingestion Experience with low-latency NoSQL datastores (e.g., DynamoDB, HBase, Cassandra, MongoDB) is a plus; experience with stream processing (Spark Streaming, Flink) is a plus Excellent interpersonal and communication skills and ability to influence at all levels Strategic mindset with the ability to influence short- and long-term strategy for maximum business impact Ability to use data to influence product and technology decisions within their scope Ability to quickly understand new technical landscapes and drive immediate impact
#J-18808-Ljbffr