About the role
About Us: EvolutionIQ’s mission is to improve the lives of injured and disabled workers and enable them to return to the workforce, saving billions of dollars in avoidable costs and lost productivity to the US and global economies and make insurance more affordable for everyone. We are currently experiencing massive growth and to accomplish our goals, we are hiring world-class talent who want to help build and scale internally, and transform the insurance space. Our team is our #1 priority, and we have been named one of Inc.’s Best Workplaces 3 years in a row! The Adventure: We're the leading AI Guidance Platform in the insurance industry today, working with some of the largest insurance carriers in the US and expanding globally. We are seeking a highly skilled and motivated Senior Analytics Engineer to play a pivotal role in building and scaling our next-generation analytical data platform. This role will be instrumental in shaping our analytics strategy, designing robust data models, and ensuring the availability, accuracy, and performance of our business intelligence data assets. As a key member of our team, you will collaborate closely with data scientists, analysts, and other engineers to deliver data-driven insights that drive critical business decisions.
Responsibilities: Platform Design and Development: Lead the design, development, and implementation of a scalable, reliable, and efficient analytical data platform. Influence decisions on technology and tool selection for data ingestion, storage, transformation, and analysis for the analytics platform. Contribute to the overall data architecture and strategy, ensuring alignment with business needs and best practices. Data Pipeline Engineering: Build and maintain robust ETL/ELT pipelines to ingest, transform, and load data from various sources into the data warehouse (e.g., cloud storage, databases, APIs). Develop and optimize data models for analytical use cases, ensuring data quality, consistency, and accessibility. Data Quality and Governance: Establish and enforce data quality standards and processes to ensure data accuracy and integrity. Implement data governance policies and procedures to manage data access, security, and compliance for analytics use cases Proactively identify and address data quality issues, working with stakeholders to resolve root causes. Collaboration and Communication: Partner with data scientists, analysts, and other engineers to understand their data needs and provide solutions. Effectively communicate technical concepts and designs to both technical and non-technical audiences. Mentor and guide data engineers, fostering a culture of learning and collaboration. Innovation and Continuous Improvement: Stay up-to-date on the latest trends and technologies in data engineering and analytics. Identify opportunities to improve existing data processes and tools. Proactively propose and implement innovative solutions to address data challenges. Required