Staff Analytics Engineer
Intuit
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
Join the Intuit Customer Success team as a Staff Analytics Engineer within our Expert Network. In this role, you will drive the data enablement strategy for our product support and live experiences. You’ll be central in optimizing our greatest resource—our people—through innovating, experimenting, learning, pivoting, and scaling.
As a Staff Analytics Engineer, you will join our team of Analytics Engineers, Data Analysts, and Data Scientists to develop tools, define metrics, and build robust Data/AI infrastructure that informs critical business decisions. You will also partner closely with Engineering leadership, Strategy, Planning, & Analysis teams, to shape and execute the overarching Analytics and AI strategy.
Responsibilities
Big Data Platform Development: Architect, design, and build fault-tolerant, scalable big-data platforms that support high-velocity, high-volume data use cases.
Cross-Functional Collaboration: Partner with Analytics, Data Science, and Central Data Engineering teams to ensure the platform meets immediate needs and remains extensible for future capabilities.
Data Architecture: Create and maintain scalable solutions for data normalization, lineage, governance, ontology, and discoverability, ensuring seamless integration across multiple systems and potentially different business units.
Data & AI Enablement: Work with analysts and data scientists to identify, prepare, and maintain datasets required for advanced analytics (GenAI, ML) and actionable customer insights.
Production-Ready ML Solutions: Collaborate with scientists and engineers to design and deploy scalable machine learning solutions, moving algorithms from concept through to production within Intuit’s platform. Possess a broad understanding of ML fundamentals, end-to-end pipelines, and common challenges such as model explainability and scalable deployment.
Engineering Best Practices: Conduct code reviews, drive coding best practices, and champion processes for unit testing, CI/CD, performance testing, capacity planning,documentation, monitoring, alerting, and incident response. Lead by example and foster a culture of continuous learning, guiding junior team members on technical excellence and collaborative problem-solving.
Qualifications
- 8+ years of relevant experience with at least 5+ years in the big-data domain
- Experienced in engineering data pipelines and ETL in languages like SQL and workflow orchestration tools. Architecting E2E big data and analyticalplatforms
- Fluent in at least one analytics and scripting language like Python.
- Passionate about using data to help guide strategic decision making.
- Experienced in building strong relationships with stakeholders and colleagues to tackle big, cross-functional problems.
- An exceptional communicator with both technical and non-technicalaudiences.
- Comfortable with ambiguity, and thrive with minimal oversight and process.
- Experience with Big-Data Technologies (Hive, HBase, Spark, Kafka, Storm,MapReduce, HDFS, Splunk, Zookeeper, MemSQL, Cassandra, Redshift,GraphDB), understands the concepts and technology ecosystem around bothreal-time and batch processing in Hadoop.
- BE/BTech/MS in Computer Science (or equivalent)
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 $163,000-220,500, Southern California $158,000-214,000. 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.