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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