Data Quality Engineer (Databricks & SQL Server) Remote (OH, USA) Contract

Role: Data Quality Engineer (Databricks & SQL Server) Location: 100% Remote - EST Time Type: Long-Term Contract Overview: We are seeking a Data Quality Engineer with strong experience in Databricks, SQL Server, and test automation to ensure the accuracy, consistency, and reliability of enterprise data. The ideal candidate will have a solid understanding of data validation frameworks, Python-based automation, and data quality processes, preferably in the healthcare domain. Key Responsibilities: • Design and implement data validation and quality frameworks using tools like Collibra or Great Expectations. • Develop and maintain automated data testing solutions across data pipelines and warehouse environments. • Perform data profiling, anomaly detection, and root-cause analysis to identify data issues proactively. • Create and execute SQL and Python scripts for data validation and reconciliation in Databricks and SQL Server. • Collaborate with Data Engineering, Analytics, and QA teams to define and enforce data quality standards. • Document test plans, validation rules, and quality metrics to support audit and governance requirements. • Support continuous improvement by developing reusable testing frameworks and data quality dashboards. Required Skills & Experience: • Overall IT Experience: 8-12 Years. • 5+ years of experience in Data Quality Engineering, Data Validation, or Data Testing. • Strong hands-on experience with Databricks and SQL Server for data validation. • Expertise in Python and SQL for automation and data analysis. • Experience with data validation and governance tools (e.g., Collibra, Great Expectations). • Proficiency in test automation frameworks (e.g., PyTest, Robot Framework). • Experience in data profiling, anomaly detection, and data reconciliation techniques. • Strong documentation and reporting skills with focus on quality metrics and process improvement. Preferred Qualifications: • Experience in Healthcare data validation or HIPAA-compliant environments. • Understanding of ETL processes, data lineage, and data pipeline testing. • Familiarity with cloud data platforms (Azure, AWS, or GCP). Soft Skills: • Strong analytical and problem-solving mindset. • Excellent communication and collaboration skills. • Detail-oriented, proactive, and process-driven approach to quality assurance.