Data Engineer

Overview We are looking for a Data Engineer to design and build scalable data pipelines while supporting the architecture and optimization of a modern cloud data warehouse. This role will focus on ingesting data from multiple sources, transforming it into reliable datasets, and ensuring it is efficiently structured for downstream analytics and reporting. This is a 6 month, full remote, rolling contract. This role is paying $70-$80 W2 $80-$90 LLC Key Responsibilities • Design and develop scalable ETL/ELT pipelines to ingest data from APIs, SaaS platforms, and internal systems • Build and maintain data workflows for batch and near-real-time processing • Develop data transformation logic using SQL and Python within the warehouse environment • Optimize data warehouse performance, storage design, and query efficiency • Implement data quality checks and monitoring across ingestion and transformation layers • Collaborate with analytics teams to ensure datasets are reliable and properly structured for downstream use • Maintain documentation and best practices for pipeline development and warehouse modeling Required Experience • Strong experience building data pipelines using Python and SQL • Hands-on experience with modern cloud data warehouses (Snowflake, BigQuery, or Redshift) • Experience with workflow orchestration tools such as Airflow or Prefect • Experience processing large datasets using Spark or distributed data frameworks • Strong understanding of data modeling and warehouse design principles • Experience integrating data from APIs, databases, and SaaS applications Nice to Have • Experience working in high-volume data environments • Familiarity with dbt for transformation workflows • Exposure to machine learning data pipelines Tech Stack Example • Python • SQL • Snowflake / BigQuery • Airflow • Spark / PySpark • Cloud (AWS or GCP)