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.
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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.
Apply tot his job
Apply To this Job
Apply tot his job
Apply To this Job