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Senior Engineer - Data Analytics

Geico

$95,000 - $230,000

Sep 3, 2025

Springfield, VA, USA • Indianapolis, IN, USA • Cheektowaga, NY, USA • San Francisco, CA, USA • Lakeland, FL, USA • Fredericksburg, VA, USA • Virginia Beach, VA, USA • Chicago, IL, USA • Annapolis, MD, USA • Macon, GA, USA • Union City, NJ, USA • Jacksonville, FL, USA • San Diego, CA, US • Richardson, TX, USA • Tucson, AZ, USA • Katy, TX, USA • Bethesda, MD, USA

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GEICO is seeking to transform its IT model to a tech organization with engineering excellence as its mission, requiring experienced Senior Engineers to build high-performance, low maintenance, zero-downtime data solutions and drive insurance business transformation.

Requirements

Advanced programming experience and big data experience within Python, SQL, dbt, Spark, Kafka, Git, Containerization (Docker and Kubernetes)
Advanced experience with Data Warehouses (Snowflake preferred), dimensional modeling, and analytics
Demonstrable knowledge of business intelligence tools (Power BI and Apache Superset preferred)
Experience with Apache Iceberg for managing large-scale tabular data in data lakes is a plus
Experience with orchestration tools such as Apache Airflow or similar technologies to automate and manage complex data pipelines
Experience architecting and designing new ETL and BI systems
Experience with CI/CD to ensure smooth and continuous integration and deployment of data solutions

Responsibilities

Scope, design, and build scalable, resilient distributed systems
Utilize programming languages like Python, SQL, and NoSQL databases, along with Apache Spark for data processing, dbt for data transformation, container orchestration services such as Docker and Kubernetes, and various Azure tools and services
Utilize your passion for data exploration to produce high quality reports with tools such as Power BI and Apache Superset to empower outstanding business decisions
Use your technical expertise to shape product definitions and drive towards optimal solutions
Lead in design sessions and code reviews with peers to elevate the quality of engineering across the organization
Manage data pipelines, ensuring consistent data availability
Consistently share best practices and improve processes within and across teams

Other

Engage in cross-functional collaboration throughout the entire development lifecycle
Mentor other engineers
Ability to balance the competing needs of multiple priorities and excel in a dynamic environment
Advanced understanding of DevOps concepts including Azure DevOps framework and tools
Knowledge of developer tooling across the data development life cycle (task management, source code, building, deployment, operations, real-time communication)