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# FBS (Mexico) Data Engineer

- **Company:** Farmers Insurance
- **Location:** United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Query Performance, Application Programming Interfaces (APIs), Agile Methodology, Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Computing, Cloud Database, Data Architecture, Information Engineering, Data Infrastructure, Data Integration, Data Systems, Data Warehousing, Database Development, Dimensional Modeling, Python (Programming Language), Operational Data Store, Performance Tuning, Cloud Services, DataOps, SQL Databases, Systems Integration, Enterprise Data Management, Data Processing, Cloud Platform System, Snowflake, Pyspark, AWS Glue, Restful APIs, Data Pipelines, Databricks
- **Published:** October 14, 2026
- **Apply:** https://jobs.farmersinsurance.com/talentcommunity/apply/1374757357/?locale=en_US

## About the Role

* 7-9 years of total professional experience.
 * 4-6+ years of experience in Data Engineering, Analytics Engineering, Data Integration, or related disciplines.
 * Fluent English (written and verbal).
 * Bachelor's degree in a technical, engineering, quantitative, or related discipline preferred.
 * Experience working in cloud-based data environments.
 * Strong stakeholder management and communication skills.

Technical Skills

Required:

 * Python (4-6 years)
 * AWS Glue
 * PySpark
 * SQL Development
 * Data Warehousing
 * REST API Integration
 * Data Modeling & Data Analysis
 * Data Pipeline Development
 * Cloud Data Platforms

Preferred/Nice-to-have:

 * AWS ecosystem experience
 * Data Catalog technologies
 * Experience with Life Insurance data environments
 * Experience supporting analytical and operational data products
 * Experience working with external vendors and TPAs
 * Cloud or Data Engineering certifications (AWS, Azure, Snowflake, Databricks, Dremio, GCP, etc.)
 * Enterprise Data Integration
 * Solution Design & Data Architecture
 * Dimensional Modeling
 * Query Performance Tuning

Business Knowledge

 * Ability to partner effectively with technical and non-technical stakeholders.
 * Strong communication and stakeholder management capabilities.
 * Experience translating business requirements into scalable technical solutions.
 * Ability to lead technical discussions and provide subject matter expertise.
 * Experience working within regulated industries preferred.
 * Life Insurance industry experience is a strong plus.
 * Ability to balance hands-on engineering work with stakeholder engagement and project leadership.

## Description

The Life Data Platform (LDP) & Data Enablement team is responsible for acquiring, integrating, governing, modeling, and publishing enterprise data across on-premises and cloud platforms. The team enables trusted, scalable, and business-ready data products, analytics, reporting, and operational insights for Life Insurance functions through modern cloud-based data technologies and data engineering practices.

The Data Engineer will be responsible for designing, developing, and supporting scalable data pipelines, data models, and enterprise data products that drive reporting, analytics, and operational business capabilities. This role combines hands-on data engineering with stakeholder engagement, working closely with business partners, analytics teams, technology teams, and external vendors to deliver high-quality data solutions and establish a trusted source of enterprise data., * Design, develop, and maintain scalable data pipelines and data integration solutions.

 * Build and support enterprise data products for analytics, reporting, and operational use cases.
 * Develop and maintain data models, data warehouses, and dimensional modeling solutions.
 * Integrate data from internal systems, cloud platforms, APIs, and third-party vendors.
 * Collaborate with business stakeholders to gather requirements and translate business needs into technical solutions.
 * Ensure data quality, governance, reliability, and consistency across platforms.
 * Optimize SQL queries and data processing performance.
 * Support cloud-based data platforms and modern data engineering frameworks.
 * Partner with external vendors and cross-functional teams to deliver successful data initiatives.
 * Provide technical leadership, mentoring, and guidance on data engineering best practices.
 * Support project planning, estimation, and execution in Agile environments.
 * Drive continuous improvements in data architecture, automation, and data platform capabilities.