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

Position: Senior Data Engineer (AWS, Redshift, SQL, Snowflake) Mode: Contract - long term Location: 100% Remote - available for EST business hours We 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, & Remediation Governance, 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.