Sr. Data Engineer (AWS, Redshift, SQL, Snowflake) - W2 Role

Position: Senior Data Engineer (AWS, Redshift, SQL, Snowflake)Mode: Contract - long termLocation: 100% Remote - available for EST business hoursWe use Tableau and Quicksight for Data Analysis; Apache Spark for Big Data Processing; and they should have used at least one AI tool: Amazon Q; Google Cloud AI; Google Cloud Smart Analytics; Tableau AI In this role you will: Data Quality Engineering & Monitoring Investigation, Analysis, & RemediationGovernance, Documentation, & Team Success About You BS degree in Engineering, Computer Science, or related field / equivalent experience 10+ years of general experience in quality testing Strong SQL skills and experience writing complex queries to analyze, validate, and troubleshoot data across multiple systems. Professional experience in data engineering, analytics engineering, data quality, software Engineering, or a related field with a strong focus on data investigation and validation. Exposure to AI-assisted development tools (e.g., GitHub Copilot, Claude) and hands-on experience applying to build and deploy AI agents that automate data pipelines, write code and testing workflows. Experience working with cloud data platforms and tools such as AWS, Redshift, Athena, Snowflake, Databricks, or similar technologies. Proficiency in Python or type script language used for automation, testing, and data analysis. Experience designing or maintaining data quality checks, monitoring, alerting, or observability processes for production datasets or pipelines. Strong understanding of data structures, data modeling, transformations, lineage, and common sources of data defects. Ability to investigate issues across systems, apply business logic, and translate ambiguous problems into structured analysis and action. Experience working with BI/reporting tools such as Tableau, QuickSight, or similar platforms is helpful. Strong communication, documentation, and collaboration skills, with the ability to work effectively across technical and non-technical teams. A learner’s mindset, curiosity about emerging technologies and AI-enabled tools, and a drive to improve systems and processes continuously. Ability to support high-priority operational periods and respond effectively to production data issues when needed. Strong interpersonal and consultative skills. Highly self-motivated and directed, with keen attention to detail. Strong leadership skills and customer satisfaction orientation.