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
Come join the Intuit Data Exchange team as a Senior Backend Developer.
Our Backend Teams are responsible for acquiring millions of transactions and statements a day to satisfy our customers needs in all Intuit products.
You will be developing high volume services that are part of Intuits Data Exchange platform.
You will utilize your skills to help develop and maintain critical backend systems in cloud environments that are vastly used by various customers, both internal and external.
#LI-Hybrid
Responsibilities
Gathering functional requirements, developing technical specifications, and project & test planning
Designing/developing SaaS software, prototypes, or proofs of concepts
Act in a technical leadership capacity: Mentoring junior engineers, new team members, and applying technical expertise to challenging programming and design problems
Roughly 70-85% hands-on coding
Resolve defects/bugs during QA testing, pre-production, production, and post-release patches
Work cross-functionally with various Intuit teams: product management, QA/QE, various product lines, or business units to drive forward results
Contribute to the design and architecture of the project
Experience with Agile Development, SCRUM, or Extreme Programming methodologies
Requirements: You have at least 5 years of active Java experience.
You have hands-on experience developing applications using Spring/SpringBoot framework and relational/non-relational DBs.
Deep understanding and experience with Kafka and Flink for real-time data processing.
Proficient in big data technologies including Apache Flink, Apache Kafka, and Apache Spark, with a strong focus on real-time data processing.
Demonstrated ability in data analysis and machine learning techniques essential for identifying fraudulent patterns and behaviors.
Expertise in both SQL and NoSQL databases, with proven experience in designing and managing large-scale database systems.
Strong programming skills in Java, Python, or Scala.
Advantage:
In-depth knowledge of fraud detection processes within the applicable industry, along with a firm grasp of compliance and security protocols.
ML, LLM, AI engineering, Agentice AI
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