The role involves building and scaling ETL pipelines to support analytics and business decision-making. The individual will monitor existing data jobs, resolve failures, and ensure data quality across various datasets. Responsibilities include optimizing SQL queries and enhancing data models to improve performance and scalability. The position requires developing new data pipelines from scratch by translating business requirements into technical solutions. The professional will collaborate closely with both business stakeholders and technology teams to manage data initiatives.

The role requires 35 years of experience in data engineering or a related field. Candidates must possess strong hands-on proficiency in Python and advanced SQL, along with experience in designing ETL pipelines and data transformations. Solid knowledge of dimensional data modeling and cloud-based data platforms is necessary. Additionally, the position requires the ability to analyze data flows and effectively communicate with stakeholders to gather requirements.