Contact Center Data Engineer I

GEICO•Bethesda, MD

1d•$86,100 - $141,450•Hybrid

About The Position

The Contact Center Data Engineer I plays a critical role in improving contact center performance by turning operational, customer, and system data into reliable insights, reporting, and automation opportunities. This role supports the analytics needs of contact center operations, interactive voice response (IVR), self-service, workforce management, product, and technology partners. The ideal candidate combines strong technical skills with practical business judgment and can use data to proactively identify issues, explain performance trends, and recommend actions that improve customer experience, operational efficiency, and business outcomes. This is a hybrid position, requiring on-site presence 2-3 days a week at one of the following locations: Dallas, TX; Palo Alto, CA; Bethesda, MD.

Requirements

1+ years of experience in business analytics, data analytics, product analytics, operations analytics, or a related analytical role.
1+ years of experience querying complex data sets using SQL and performing data analysis.
1+ years of experience using analytical or programming languages such as Python, R, SAS, .NET, M, or DAX.
Experience developing reporting or data visualizations in Power BI, Amazon QuickSight, Tableau, or similar business intelligence tools.
Ability to work with large and complex data sets, validate results, and explain findings in a clear and business-focused way.
Ability to manage multiple priorities, follow established processes, learn technical concepts quickly, and work effectively in a cross-functional environment.
BA/BS degree in computer science, statistics, analytics, operations research, economics, mathematics, or a related field.

Nice To Haves

Experience supporting contact center, IVR, customer service, workforce management, digital servicing, insurance, or financial technology environments.
Experience using Amazon CloudWatch or similar monitoring tools to identify system, service, or operational anomalies.
Experience working in an Agile environment with product, engineering, or technology teams.
Working knowledge of data governance, metric definition, data quality validation, and documentation practices.
Interest in automation, self-service improvement, and translating analytics into measurable business value.

Responsibilities

Develop, test, deploy, and maintain data structures, enterprise reports, dashboards, data visualizations, analytical systems, and recurring performance reporting.
Analyze contact center, IVR, digital, customer, and operational data to identify trends, root causes, performance gaps, and opportunities for automation or process improvement.
Build and maintain reporting using Power BI, SQL, Amazon QuickSight, Amazon CloudWatch, and other approved analytics tools used by the team.
Monitor key operational metrics and proactively identify emerging issues, including changes in call volume, containment, transfer behavior, speed of answer, abandonment, handle time, call drivers, and customer experience indicators.
Partner with operations, workforce management, IVR, automation, product, technology, data architecture, and data governance teams to understand business problems, define requirements, and design practical data solutions.
Research and query structured and unstructured data sources to understand how systems work, validate data quality, and expand available reporting and insight capabilities.
Create clear documentation for code, reporting logic, metric definitions, source systems, data structures, and operational assumptions.
Serve as a data steward for assigned subject areas, helping ensure data is accurate, available, properly classified, and governed appropriately.
Communicate findings clearly to technical and non-technical audiences, translating complex data into practical business recommendations.