Intuit is looking to leverage big data technologies to gain new insights into customer experiences, building data frameworks, ingestion pipelines, and tools to power prosperity for people and communities.
Requirements
- Proficiency in developing Software for Java (Spring & Springboot), Scala for spark streaming & spark applications, or other JVM based languages.
- Expert Knowledge of SQL, XML, JSON, YML, very strong Python and Linux
- Proficiency with tools and frameworks Docker, Spark, Scala, Jupiter Notebook, Databricks Notebooks, Kubernetes, Feature Management Platforms, SageMaker
- Strong background using cloud platforms such as AWS, Azure or GCP - Amazon web services: EC2, S3, and EMR (Elastic Map Reduce) or equivalent cloud computing approaches
- Strong expertise in Data Warehousing and analytic architecture and working with large data volumes, data visualization
- Experience with low-latency NoSQL datastores (such as DynamoDB, HBase, Cassandra, MongoDB) is a plus
- Experience with building stream-processing applications using Spark Streaming, Flink, etc. is a plus
Responsibilities
- 70-85% hands-on development in all phases of the software life cycle.
- Rapidly fix bugs and solve problems
- Conduct design, code reviews and defect remediation
- Create technical design specification and implement data models for analytics, reporting, and machine learning workflows
- Lead, estimate work for initiatives and sequence of individual activities as inputs to project plans
- Clean, transform and validate data for use in analytics and reporting
- Optimize data processing for performance, cost and reliability while monitor data quality and pipeline performance, troubleshoot and resolve data issues
Other
- BS or MS in Computer Science, Data Engineering or related field or equivalent experience
- 6+ years of core development experience with data engineering experience
- Influences and communicates effectively with non-technical audiences including senior product and business management.
- Collaborates effectively with peer engineers, data scientist, analyst and architects to solve complex problems
- Actively stay abreast of industry best practices, share learnings, and experiment and apply cutting edge technologies
