Data Analytics Engineer

Allstate Insurance Co. is dedicated to protecting families and their belongings from life’s uncertainties. The Data Analytics Engineer will be responsible for developing data infrastructure projects and proof of concept business solutions, collaborating with data scientists and analytic engineers to meet business needs.

Responsibilities:

• Builds test scripts, executes testing, works with data scientists and business to ensure end user acceptance
• Leverage 'agile' data analysis with technology fluency in parallel processing/programming, software/programming languages and technologies (i.e. Oracle, SQL, Python and Spark), paired with a high degree of analytic agility to be able to meet fluid and dynamic business needs in this space
• Execute rapid development of new data and analytic work tracks with fast iteration over quick sprints
• Help develop and deliver the data infrastructure required to support needs of predictive modeling and analytics with minimal supervision
• Mentor other team members in a business technical environment and promote an environment that supports innovation and process improvement
• Participate in the development of enterprise data assets, information platforms or data spaces designed for exploring and understanding the data
• Participate in the development of new concepts, proof of concept designs, and prototypes for business or research data solutions so that business users or predictive modelers may visually understand and explore a new feature or functionality before implementation to expose design assumptions and drive ideation
• Work with Data Scientists and business partners on cross functional teams; developing subject matter expertise in the business as well as advanced analytics
• Provide support on requirement development for analytic data sources, breaking down business problems into solvable components and assist with documenting requirements with minimal supervision

Requirements:

• 2 or more years of experience
• Builds test scripts, executes testing, works with data scientists and business to ensure end user acceptance
• Leverage 'agile' data analysis with technology fluency in parallel processing/programming, software/programming languages and technologies (i.e. Oracle, SQL, Python and Spark), paired with a high degree of analytic agility to be able to meet fluid and dynamic business needs in this space
• Execute rapid development of new data and analytic work tracks with fast iteration over quick sprints
• Help develop and deliver the data infrastructure required to support needs of predictive modeling and analytics with minimal supervision
• Mentor other team members in a business technical environment and promote an environment that supports innovation and process improvement
• Participate in the development of enterprise data assets, information platforms or data spaces designed for exploring and understanding the data
• Participate in the development of new concepts, proof of concept designs, and prototypes for business or research data solutions so that business users or predictive modelers may visually understand and explore a new feature or functionality before implementation to expose design assumptions and drive ideation
• Work with Data Scientists and business partners on cross functional teams; developing subject matter expertise in the business as well as advanced analytics
• Provide support on requirement development for analytic data sources, breaking down business problems into solvable components and assist with documenting requirements with minimal supervision