About the job
About Us
At Abacus Insights, we are revolutionizing data utilization for health plans. Our mission is clear: to make healthcare data actionable, empowering decision-makers with the insights they need to respond swiftly and confidently.
We dismantle data silos, establishing a cohesive data foundation that enables improved decision-making, ultimately enhancing outcomes, minimizing waste, and enriching the experiences of both members and providers.
Supported by $100 million from leading investors, we are addressing significant challenges in an industry ripe for transformation. Our platform fosters GenAI applications by providing clean, interconnected, and reliable healthcare data that underpins automation, prioritization, and decision workflows, positioning us at the forefront of innovation.
Our success starts with our people. We value boldness, curiosity, and collaboration, believing that the best ideas emerge from teamwork. Are you ready to make a difference? Join us in building the future.
About the Role:
We are looking for a skilled Senior Data Quality Assurance Engineer to spearhead the development and implementation of robust data quality testing strategies across our platforms and data pipelines. You will be responsible for ensuring the integrity, accuracy, and reliability of our data ecosystem through sophisticated testing methodologies and automation frameworks.
Your Daily Responsibilities:
- Design and implement comprehensive data quality testing strategies for data pipelines, ETL/ELT processes, and data warehouses.
- Create automated data validation frameworks to confirm data accuracy, completeness, and consistency.
- Establish and maintain data quality metrics, monitor dashboards, and set up alert mechanisms.
- Execute complex SQL queries to validate data transformations and business logic.
- Craft test cases for data ingestion, processing, and consumption layers.
- Work collaboratively with data engineers, data scientists, and analysts to grasp data requirements and quality standards.
- Lead root cause analysis for data quality issues and implement preventive measures.
- Mentor junior QA engineers and promote data testing best practices.
