Data Quality Engineer

Data Quality Engineer

About the Role

We are seeking a meticulous and results-oriented Data Quality Engineer to join our healthcare technology team leveraging AWS. In this critical role, you will be responsible for ensuring the accuracy, consistency, and completeness of data across our cloud-based healthcare solutions. You will design, develop, and implement automated solutions to monitor and improve data quality throughout the entire data lifecycle, directly impacting patient care and healthcare research.

Responsibilities

• Design and implement data quality frameworks and processes within AWS services.
• Experience and project completion in terms of Data Quality metric – Accuracy, Timeliness, Validity, Completeness, Uniqueness
• Working with 3rd party tools like Collibra, IDQ , Infospere for data quality metrics
• Develop and maintain automated data quality checks using SQL, Python, and PySpark to ensure data adheres to internal quality standards.
• Monitor data pipelines for anomalies and identify potential data quality issues that could impact our KPIs
• Investigate and troubleshoot data quality problems, root causing issues and proposing solutions to ensure data integrity.
• Collaborate closely with data engineers, data scientists, and healthcare professionals to define data quality requirements for patient data and develop solutions that meet industry best practices.
• Document data quality processes and standards to ensure ongoing compliance and data governance.
• Stay up-to-date on the latest data quality tools, methodologies, and healthcare data regulations.

Qualifications

• 5-8 years of experience in data engineering, data quality, or a related field, with a focus on healthcare data is a plus.
• Familiarity with AWS services, particularly AWS Glue, AWS Redshift, lambda, AWS Data Pipeline
• Proven experience in designing and implementing data quality solutions
• Strong analytical and problem-solving skills with a keen eye for detail.
• Expertise in SQL for querying and manipulating healthcare data.
• Proficiency in Python and PySpark for data processing and analysis of patient information.
• Excellent communication and collaboration skills to work effectively with both technical and non-technical stakeholders in the healthcare field.

Bonus Points

• Experience with healthcare data quality tools specific to the industry.
• Experience with data governance and data lineage in a healthcare setting.