Senior Data Engineer

Key Responsibilities Architect & Model: Design, implement, and maintain scalable data models using Star, Snowflake, and Data Vault methodologies. Optimize BigQuery: Write, refactor, and optimize complex, highly efficient SQL queries with a strong focus on cost reduction, execution time, and concurrency. Build ELT/ETL Pipelines: Design, test, and deploy robust data ingestion and transformation pipelines (primarily using GCP Data Fusion / Apache Airflow). Integrate Diverse Sources: Connect and wrangle data from various sources, including RESTful/SOAP APIs and SFTP servers, handling formats like JSON, CSV, and XML. Drive DataOps Culture: Collaborate within an Agile framework using Git and CI/CD pipelines to ensure automated testing and continuous delivery of data solutions. Technical Requirements 3+ years of expert-level SQL & BigQuery hands-on experience (complex optimization, cost control, data integrity). 3+ years of experience in ELT/ETL pipeline development using GCP Data Fusion (highly preferred) or Apache Airflow. Strong expertise in Data Modeling & Architecture – deep understanding of Kimball/Inmon concepts and hands-on experience with Data Vault (major plus). API & Data Ingestion proficiency – proven track record of ingesting and parsing JSON, XML, and CSV data from REST/SOAP endpoints. Git & CI/CD fluency – practical knowledge of version control and continuous testing/delivery tools in cloud environments.