Das ist der Job
AWS CUR).
Darum lohnt es sich
Expertise in designing efficient and scalable data models with large data sets across multiple teams and in collaboration with insights or data stakeholders.
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.
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. Requirements 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. Demonstrated ability to operate as Lead Individual Contributor and work cross‑functionally. Demonstrated experience mentoring and developing less senior engineers. NICE TO HAVE: Experience processing cloud billing data (e.g.
AWS CUR, Azure Cost Management) or complex financial datasets. Proficiency in cloud infrastructure (AWS or GCP). #J-18808-Ljbffr
