Senior Staff Engineer – Finance Data - Remote

Senior Staff Engineer – Finance Data

Position Summary

It is an exciting time to be at GEICO as we transform the insurance business and build a tech organization with engineering excellence as its mission, with a culture of psychological safety and continuous improvement. We are seeking experienced engineers with a passion for building high-performance, low maintenance, and zero-downtime systems to help us build a Finance Data Lake from the ground up. 

Position Description

Our Senior Staff Engineer works with our Staff and Sr. Engineers to innovate and build new systems, improve and enhance existing systems and identify new opportunities to apply your knowledge to solve critical problems. You will lead the strategy and execution of a technical roadmap that will increase the velocity of delivering products and unlock new engineering capabilities. The ideal candidate has deep technical expertise.

Position Responsibilities

As a Senior Staff Engineer, you will:

• Define the engineering direction and roadmap for the new Finance Data Lake that aligns with business goals.
• Lead the development of our new Finance Data Lake meeting goals for security, resilience, compliance and correctness. 
• Provide technical guidance and mentorship to team members, sharing knowledge and best practices to foster a culture of constant learning.
• Hold a high bar on technical decision making, and setting a standard for engineering artifacts that the team creates, such as code and design docs.
• Stay up-to-date with industry trends and emerging technologies, evaluating their potential impact on the payments engineering domain and making recommendations for adoption.
• Triage and resolve service disruptions, and build industry standard mechanism for prevention and self-healing.
• Influence and educate leadership at all levels.

Qualifications

• Exemplary ability to design and develop, perform experiments, and influence engineering direction and product roadmap
• Advanced experience developing new and enhancing existing data processing (data ingestion, data transformation, data storage, data management, data quality) components
• Understanding of data warehouse concepts including data modeling and OLAP
• Experience working with cloud data solutions (Delta Lake, Iceberg, Hudi, Snowflake, Redshift, or equivalent)
• Experience with data formats such as Delta, Parquet, Avro, ORC, XML, JSON
• Experience working streaming applications (Spark Streaming, Flink, Kafka, or equivalent)
• Data processing/data transformation using ETL/ELT tools such as DBT (Data Build Tool), or Databricks
• Understanding of machine learning
• Strong working knowledge of SQL and the ability to write, debug and optimize SQL queries and ETL jobs to reduce the execution window or reduce resource utilization
• Experience with cloud computing …