Staff Data Engineer- cost and usage data - Remote
Staff Data Engineer, Technology Strategy & Ops
Role Description
As a Staff Data Engineer within the Technology Strategy & Ops team supporting Central Technology, you will act as a hands-on technical lead to design, build, and maintain scalable data pipelines and models that power critical data products and processes, including technology cost and usage dashboards, customer monthly business reviews, cost optimization efforts and monthly financial technology usage attributions. All of these support the efficient use of technology. You will collaborate with technologists, strategists and finance specialists to ensure our data infrastructure is reliable and performant.
Responsibilities
Actively design, build, and optimize scalable ETL pipelines for structured and semi-structured data supporting Insights and Finance use cases that analyze technology usage and costs (e.g. AWS CUR).
Design and implement complex data models using industry best practices that capture a complete view of technology usage and costs, while ensuring accuracy, scalability, and long-term usability.
Partner closely with internal stakeholders to understand their needs and craft solutions that drive their ultimate outcomes.
Architect and implement robust, maintainable, and high-performance data solutions.
Automate workflows to reduce manual intervention and enhance data processing efficiency, including automation for finance processes.
Mentor junior data engineers through code reviews and technical guidance, setting best practices and fostering technical growth.
Optimize query performance and resolve pipeline bottlenecks to improve data accessibility.
Ensure data quality and governance.
Required Qualifications
Bachelor's or Master s degree in Computer Science, Information Systems, Engineering, or a related field.
6+ years experience in data engineering or a related field.
Expert-level hands-on coding skills, specifically in Python, SQL, and tools like Airflow, Databricks and dbt.
Expertise in designing efficient and scalable data models with large data sets across multiple teams and in collaboration with insights or data stakeholders.
Demonstrated ability to operate as Lead Individual Contributor and work cross-functionally.
Demonstrated experience mentoring and developing less senior engineers.
Desired Qualifications
Experience processing cloud billing data (e.g. AWS CUR, Azure Cost Management) or complex financial datasets
Proficiency in cloud infrastructure (AWS or Google Cloud Platform)
Role Description
As a Staff Data Engineer within the Technology Strategy & Ops team supporting Central Technology, you will act as a hands-on technical lead to design, build, and maintain scalable data pipelines and models that power critical data products and processes, including technology cost and usage dashboards, customer monthly business reviews, cost optimization efforts and monthly financial technology usage attributions. All of these support the efficient use of technology. You will collaborate with technologists, strategists and finance specialists to ensure our data infrastructure is reliable and performant.
Responsibilities
Actively design, build, and optimize scalable ETL pipelines for structured and semi-structured data supporting Insights and Finance use cases that analyze technology usage and costs (e.g. AWS CUR).
Design and implement complex data models using industry best practices that capture a complete view of technology usage and costs, while ensuring accuracy, scalability, and long-term usability.
Partner closely with internal stakeholders to understand their needs and craft solutions that drive their ultimate outcomes.
Architect and implement robust, maintainable, and high-performance data solutions.
Automate workflows to reduce manual intervention and enhance data processing efficiency, including automation for finance processes.
Mentor junior data engineers through code reviews and technical guidance, setting best practices and fostering technical growth.
Optimize query performance and resolve pipeline bottlenecks to improve data accessibility.
Ensure data quality and governance.
Required Qualifications
Bachelor's or Master s degree in Computer Science, Information Systems, Engineering, or a related field.
6+ years experience in data engineering or a related field.
Expert-level hands-on coding skills, specifically in Python, SQL, and tools like Airflow, Databricks and dbt.
Expertise in designing efficient and scalable data models with large data sets across multiple teams and in collaboration with insights or data stakeholders.
Demonstrated ability to operate as Lead Individual Contributor and work cross-functionally.
Demonstrated experience mentoring and developing less senior engineers.
Desired Qualifications
Experience processing cloud billing data (e.g. AWS CUR, Azure Cost Management) or complex financial datasets
Proficiency in cloud infrastructure (AWS or Google Cloud Platform)