Job Description

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.

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