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# FBS (Mexico) - Analytics Engineer (USFITFV)

- **Company:** Farmers Insurance
- **Location:** United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Airflow, Business Analytics Applications, Data Analysis, Application Frameworks, Business Logic, Big Data, Software Quality, Code Review, Continuous Integration, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Sharing, Data Systems, Data Warehousing, Python (Programming Language), Meta-Data Management, Microsoft SQL Server, Performance Tuning, Query Optimization, SQL Databases, Workflow Management Systems, Delivery Pipeline, Snowflake, Git, Data Layers, Machine Learning Operations, Software Coding, Software Version Control, Data Pipelines
- **Published:** November 14, 2026
- **Apply:** https://jobs.farmersinsurance.com/talentcommunity/apply/1377529557/?locale=en_US

## About the Role

* 3+ years of experience working as an Analytics Engineer or equivalent
 * Hands-on experience with SQL, SQL Server, Python, SnowFlake and DBT.
 * Experience in version control systems such as Git, and workflow management tools such as Airflow
 * Proven experience in designing and building scalable data pipelines.
 * Expertise in ETL/ELT processes, data modeling, and integration of data from multiple sources into a data warehouse.
 * Experience with CI/CD workflows and tools for data engineering.
 * Strong problem-solving and analytical skills, with the ability to work effectively in a collaborative environment.

## Description

Seeking a highly skilled and motivated data engineer to join Analytics Engineering team within the Service Analytics and AI organization. This role is pivotal in designing, building, and maintaining scalable data pipelines and analytics solutions that empower Advanced Analytics, Business Intelligence, and Data Science initiatives. You will play a crucial role in building a semantic data layer, defining and implementing cutting-edge data products, and delivering innovative AI-driven solutions that fuel business growth and enhance customer experience., * Data Pipeline Development: Lead the design, development, and deployment of scalable and robust data pipelines, ensuring seamless data integration and processing across diverse systems.

 * Analytics Engineering Best Practices: Establish and uphold best practices for data engineering, including coding standards, data governance, performance optimization, and automation strategies.
 * Code Quality and Review: Participate in code reviews, provide constructive feedback, and contribute to the team's continuous improvement in coding practices and methodologies.
 * ETL/ELT Development: Design, build, and maintain robust ETL/ELT pipelines, reusable frameworks, and libraries to process and transform data from diverse sources, ensuring accuracy, quality, and consistency.
 * Automation and CI/CD: Implement CI/CD pipelines to streamline the deployment, testing, and maintenance of analytics engineering processes.
 * Cross-functional Collaboration: Partner with data scientists, engineers, analysts, product managers, and business stakeholders to understand requirements
 * Stakeholder Communication: Articulate complex technical concepts to non-technical stakeholders, fostering alignment and ensuring a shared understanding of data initiatives across teams.
 * SQL & Data Engineering: Advanced SQL development, query optimization, complex transformations, and large-scale data processing.
 * Hands-on experience designing and developing enterprise-scale data solutions using Snowflake including performance tuning, data sharing, tasks, streams, and modern platform capabilities.
 * Experience building scalable transformation frameworks, reusable business logic, testing, documentation, and deployment pipelines using dbt.
 * Star schemas, conformed dimensions, historical tracking, KPI frameworks, and analytical data models.
 * Data quality, lineage, metadata management, testing, observability, and model lifecycle management.
 * Experience delivering data products within Agile product teams and modern cloud environments.

Physical Actions