Senior Data Developer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Every day, millions of people and businesses around the world rely on Intuit’s products to answer these questions. Increasingly, our users expect to converse in natural language to accomplish these tasks instead of navigating menus and windows.

Join the Conversational Experiences team as Senior Data Engineer to accelerate the next generation of conversational experiences across Intuit’s products. As part of the team, you will work with product managers, user experience designers, and data scientists to rapidly deliver tools, new data reporting capabilities to provide insights and metrics to our Chatbot designer and analytics community. Conversational Experiences is at the intersection of exciting progress in machine learning, computer science and user experience. Be ready to learn fast and boldly innovate beyond the currently accepted normal.

Qualifications

• BS/MS in computer science/data engineering or equivalent work experience
• Solid grasp of software development fundamentals and their practical application
• Strong problem solving and communication skills
• 5+ years of experience developing web applications
• Expertise in data engineering including Presto, SQL, Glue, Athena and Python.
• Working knowledge of Spark/Beam/Flink for building streaming/batch processing pipelines.
• Nice to have: Experience working with tableau.
• Nice to have: Experience with development and operations using AWS and/or Kubernetes
• Nice to have experience building chatbots
• Hungry to continuously learn
• Boldly innovate beyond what is the currently accepted

Responsibilities

• Create and maintain optimal data pipeline architecture
• Assemble large, complex data sets that meet functional / non-functional business requirements
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data technologies
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs
• Accurately scope effort, identify risks and clearly communicate trade-offs
• Proactively look for ways to improve code or automate/simplify tasks