Analytics Engineer

Mercury Insurance is a recognized leader in the insurance industry, and they are seeking an Analytics Engineer to join their Technical Product Analytics team. This role involves building and maintaining data foundations to enable insights across technical products and customer experiences, focusing on data architecture, pipeline development, and cross-functional collaboration.

Responsibilities:

• Design, build and maintain scalable dbt models and data marts supporting product analytics use case across web, mobile and agent facing platforms
• Develop a unified data model integrating event data (Segment.io)
• Implement clean metric logic (sessionization, funnels, conversions, retention) with clear definitions and metric lineage
• Build and automate ELT pipelines (using dbt) feeding the product analytics warehouse (Redshift)
• Enforce data quality through schema tests, assertions and anomaly detection frameworks
• Maintain metadata and documentation to ensure transparency in the analytics layer
• Partners with engineering teams to define data contracts and ensure reliable event instrumentation across various products
• Work closely with analysts and product managers to translation business requirements into technical data models with reusable transformations
• Build and maintain dynamic sales funnel dashboards (using PowerBI), providing real-time insights into lead progression, conversion rates, and KPIs
• Take ownership of key analytics areas, including multi-raters, aggregators, and customer behavior in the insurance sales funnel
• Apply strong knowledge of SQL, Python, and data visualization to solve complex data problems
• Leverage understanding of the insurance industry to provide meaningful insights and guide product decisions, particularly in areas related to the insurance sales process

Requirements:

• Bachelor's degree in computer science, Mathematics, Statistics, Data Science, Business Analytics, or a related field
• Alternatively, an equivalent combination of education and/or experience in product analytics, data analysis, or a related discipline
• 5+ years of experience in data analytics, analytics engineering, data engineering
• 4+ years of experience in product analytics, focusing on user behavior, engagement metrics, and product performance analysis
• Proven track record of collaborating with product teams to establish measurement tools and processes
• Strong background in developing dashboards, reporting tools, building data models
• Proficiency in SQL and Python for data analysis and building data pipelines
• Strong experience with data visualization tools (PowerBI) to create and maintain comprehensive dashboards
• Expertise in relational and non-relational databases and data sources
• Deep understanding of ETL/ELT processes and tools (e.g., dbt)
• Advanced data skills with the ability to work with large structured and unstructured data sets
• Strong analytical and creative thinking, comfortable working in ambiguous situations
• Experience in managing and communicating data strategies and models to internal stakeholders
• Demonstrated expertise in data mining
• Solid experience with cloud-based advanced data and analytics environments
• Excellent problem-solving skills and critical thinking abilities
• Strong written and verbal communication skills, capable of effectively conveying complex information
• Ability to interact and collaborate with senior management and cross-functional teams
• Passion for data-driven decision-making and continuous improvement in analytics practices
• Experience in P&C insurance