15 days ago
Base Salary
$206k - $278k/yr
Responsibilities
- Develop and maintain data products, software services, data frameworks, ingestion pipelines, data models, and reusable libraries or tools.
- Provide technical leadership across multiple scrum teams and drive complex projects, estimates, designs, implementation, troubleshooting, and lifecycle support.
- Spend approximately 70–85% of the role on hands-on software development across the software lifecycle.
- Diagnose and resolve complex cross-capability issues, rapidly fix bugs, and define durable solutions.
- Use customer behavior, funnel metrics, experimentation, and growth opportunities to guide technical investments and product decisions.
- Apply end-to-end system design principles across operational excellence, security, reliability, performance efficiency, and cost optimization.
- Mentor and assess engineers, lead technical learning sessions, support talent development, and promote inclusive collaboration.
- Collaborate with engineers, data scientists, analysts, architects, product managers, designers, and business stakeholders.
- Influence technology and product direction and communicate technical architectures and decisions to technical and non-technical audiences.
Requirements
- Bachelor’s or master’s degree in Computer Science, Data Engineering, or a related field.
- At least 9 years of software engineering experience with a strong background in data engineering.
- Expertise with Java, Spring, Spring Boot, Scala, Spark Streaming, Spark applications, or other JVM-based languages.
- At least 5 years of professional experience with SQL, XML, JSON, YAML, Python, and Linux.
- Knowledge of AI/ML, generative AI, personalization, recommendation engines, predictive modeling, and growth-focused AI/ML applications.
- Experience using GenAI tools such as Cursor or Windsurf to accelerate development and build reusable GenAI platform components.
- Expertise with Docker, Spark, Scala, Jupyter Notebook, Databricks Notebooks, Kubernetes, feature management platforms, and SageMaker.
- Experience with AWS, Azure, or Google Cloud, including AWS EC2, S3, EMR, DynamoDB, and Athena; AWS expertise is specifically noted.
- Professional experience with data warehousing, analytic architecture, large data volumes, and data visualization.
- At least 5 years of professional experience with big data technologies including Hive, Hadoop, Kafka, columnar databases, and graph databases.
- Strong experience with stream processing or near-real-time data ingestion; experience with Spark Streaming or Flink is a plus.
- Experience with low-latency NoSQL datastores such as DynamoDB, HBase, Cassandra, or MongoDB is a plus.
- Strong interpersonal, communication, strategic thinking, influence, and cross-functional collaboration skills.
Benefits
- Competitive compensation package with performance-based rewards, potential cash bonus, equity rewards, and benefits.
- Expected base pay range is $205,500–$277,500 annually for San Diego; pay varies by knowledge, skills, experience, and work location.
Tech Stack
Amazon DynamoDBApache CassandraApache FlinkApache HadoopApache HBaseApache HiveApache KafkaApache SparkAWSAzureDatabricksDockerGoogle CloudGoogle Cloud PlatformJavaJupyter NotebookKubernetesLinuxMongoDBPythonScalaSpring BootSQL
Categories
Data Engineering
About Intuit
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