Data Engineer AI

Quest Global•Sunnyvale, CA

2d•Onsite

About The Position

Quest Global delivers world-class end-to-end engineering solutions by leveraging our deep industry knowledge and digital expertise. By bringing together technologies and industries, alongside the contributions of diverse individuals and their areas of expertise, we are able to solve problems better, faster. This multi-dimensional approach enables us to solve the most critical and large-scale challenges across the aerospace & defense, automotive, energy, hi-tech, healthcare, medical devices, rail and semiconductor industries. We are looking for humble geniuses, who believe that engineering has the potential to make the impossible possible; innovators, who are not only inspired by technology and innovation, but also perpetually driven to design, develop, and test as a trusted partner for Fortune 500 customers. As a team of remarkably diverse engineers, we recognize that what we are really engineering is a brighter future for us all. If you want to contribute to meaningful work and be part of an organization that truly believes when you win, we all win, and when you fail, we all learn, then we’re eager to hear from you. The achievers and courageous challenge-crushers we seek, have the following characteristics and skills.

Requirements

Snowflake
SQL
AI integration
Agentic AI
Python
Excel
Numbers
Experience presentation/project management Tools like Quip, Keynote, Miro, Slack
Experience and understanding of machine learning tools like datarobot
Project Management experience
Good Interpersonal, relationship building, communication and presentation skills

Nice To Haves

Tableau
Create and improve data visualization tools like Tableau & ThoughtSpot
Work with Snowflake & it’s built in infrastructure
Provide support to a wide variety of business teams

Responsibilities

Perform root cause analysis on processes and data to identify opportunities for improvement and answer questions
Build processes that support data transformation, workload management, data structures, dependency and metadata
Perform data validation checks, identify and rectifying errors, and maintaining a quality standard throughout the data's lifecycle.
Explore datasets to identify trends, patterns, and insights.
Perform analysis for stakeholders and other non-technical professionals.
Build models to generate actionable insights for making efficient business decisions.
Build data pipelines that clean, transform, and aggregate data from disparate sources
Work with data to solve business problems, building and maintaining the infrastructure to answer questions and improve processes
Streamline data science workflows, adding value to our product offerings and building out the customer lifecycle and retention models