QAA Middle Data Quality Assurance Analyst

We exist to power better care.

We are on a mission to power better care​ by optimizing every patient journey​. We help payers, providers, and life sciences companies deliver better care, therapies, and outcomes by delivering the most actionable patient journey insights and value-based payments platform. With us, healthcare organizations benefit from big data efficiencies and self-service, on-demand enterprise insights that light the path to higher-value care.

Clarify seeking a Mid-level Data Quality Assurance Analyst to join our team. The successful candidate will play a crucial role in ensuring the accuracy and reliability of our data pipelines. You will be responsible for the quality assurance of data processes, building and maintaining tests, and generating reports to support data validation and enhancements.

Does this sound like you?
You are passionate about data and data quality.
You are eager to learn new healthcare related data domains.
You have an enthusiastic, energetic personality; inquiring, investigative mind.
You embrace change as an opportunity to learn.
You take great care in the details.

The Role:
The Mid-level Data Quality Assurance Analyst will be responsible for a range of responsibilities, including (but not limited to):

Conduct thorough QA of data, identifying and resolving data inconsistencies and errors.
Develop and maintain manual and/or automated tests for data validation.
Build comprehensive reports to track data quality anomalies and status.
Work closely with the data engineering team to test systems enhancements.

What we are looking for:
We are always looking for new team members who will add to our culture and have a strong passion for impact. In particular, the Mid-level Data Quality Assurance Analyst will have:
3+ years of hands-on experience in data quality assurance, focusing on validating data integrity, accuracy, and consistency.
Proficient in SQL and Python, capable of writing complex queries and scripts to automate data validation and error detection.
Experience with data validation tools and frameworks, with a strong understanding of best practices in data and software testing.
Practical knowledge of data management systems, specifically SQL databases.
Strong analytical and problem-solving skills to effectively identify and resolve data discrepancies and issues.
Proficiency in version control and collaboration tools like Git, as well as experience with workflow management tools such as JIRA.
Demonstrable knowledge and expertise reporting data quality metrics and insights.
A bachelor’s degree in computer science, Information Systems, or a related field, complemented by relevant hands-on experience in data quality roles.

We are looking forward to receiving your CV!