Manager 2, Software Engineering

Come join Intuit’s Consumer Group as a Manager 2, Software Engineering and help build Consumer Data Plane using Credit Karma and Turbotax Data to enable the data layer for AI-Native Experiences & Agents, Growth marketing, In-product personalization, Expert, 3rd Party surfaces, and Agentic Browsers. As an engineering manager, you will lead a team of software and data engineers building the next generation of AI ready data for Credit Karma and Turbotax customers.

Responsibilities

• Lead and grow a high-performing team of software & data engineers building agentic data capabilities for semantic data modeling, data pipelines and retrieval services for Consumer Data Plane using Credit Karma and Turbotax data, ensuring data quality and governance.

• Coach and mentor engineers on modern scalable data architecture focusing on semantic data modeling, data quality & governance, data ingestion, ETL patterns, data processing, data storage and data retrieval, AI-assisted skill development for 3x developer velocity, and career growth; build a strong inclusive team culture

• Bring thought leadership in AI / Gen AI, agentic systems, semantic search, knowledge graph and personalization to disrupt how consumers do their taxes, money and personal finance using Consumer Data Plane

• Provide data capabilities to Product, Marketing and AI Science teams to build data insights in Consumer Data Plane, use it to power Credit Karma and Turbotax AI-Native Experiences & Agents, Growth marketing, In-product personalization, Expert, 3rd Party surfaces, and Agentic Browsers and drive measurable improvements in engagement, approvals, tax conversions, customer benefits and NPS.

• Drive operational and engineering excellence - uptime during tax season peak load, quality, speed-to-market, developer productivity, and data-driven decision making

• Define and uphold engineering standards across the Consumer Group - code quality, CI/CD, testability, observability, SRE practices, and incident response

• Develop, maintain, and enforce data architecture standards, best practices, and design patterns to ensure consistency and quality across data capabilities

• Develop roadmap for building data capabilities that align with business objectives and overall technology strategy, and run agile delivery - quarterly OKRs, sprint planning, backlog grooming, and clear stakeholder communication to drive impact to business

• Operate effectively during the high-intensity US tax season (Jan-Apr), with strong incident and release management discipline

• Operational & Financial Accountability: Own the consumer data plane cost budget, including compute and storage costs. Build cost attribution models for Product, Marketing and AI science teams using Consumer Data Plane and plan initiatives to optimize the cost.

• BS/MS in Computer Science, Computer Engineering or equivalent work experience

• 8+ years of software development experience, including 2+ years managing software engineering teams

• Deep understanding of data modeling principles, including schema design and dimensional data modeling, with experience in writing efficient SQL queries.

• Strong background in data ingestion, processing, storage, and querying technologies: MySQL, Spanner, Spark, Flink Streaming, Bigquery, Dataflow, Airflow, Bigtable, Cassandra, Java microservices, Spring Boot, GraphQL/REST APIs and object-oriented programming languages: Python, Java, C++

• Knowledge of AI/ML and GenAI technologies - LLMs, RAG, Semantic Search (e.g Vertex AI search, AWS cloud search) and Knowledge Graph (e.g neo4j, ..) to integrate our data with generative AI experiences

• Experience building 100M+ consumer-scale data pipelines and data retrieval services for SaaS or mobile applications (consumer fintech, tax, or e-commerce a strong plus)

• 3+ years of cloud experience building and operating services on AWS / GCP; experience with Lambda, container orchestration, and serverless is a plus

• Knowledge of agile methodologies (Scrum/Kanban), CI/CD pipelines, observability, and SRE practices

• Track record of building diverse, inclusive teams and developing engineers’ careers

• Excellent communication skills - able to translate complex technical decisions for both technical and non-technical audiences

• Strong understanding of SOA, distributed systems, and event-driven architectures

• Experience working with Product, Marketing and AI Science partners to ship customer-facing features powered by data insights