Data QA Engineer
Core
Design and maintain automated data quality validation frameworks, test procedures, and monitoring for healthcare data ingestion and transformation pipelines.
Role type
Data Quality Engineer (Healthcare Data)
Builds
Automated data validation solutions, QA dashboards, and rule engines for cloud-native data management platforms.
Domain
Healthcare data, cloud data engineering, data quality frameworks.
Deliverable
production ML models | product features | dashboards & analysis
Required skills
SQL, Python, Java, data profiling, ETL/ELT pipelines, automated testing, data mining, root cause analysis, HIPAA/SOC 2 compliance knowledge.
Preferred skills
Delta Lake, Spark, Airflow, dbt, schema evolution management (Parquet, Avro, ORC, JSON), Terraform, CI/CD workflows, software debugging.
Technologies
AWS (S3, EC2, SSM, Athena), Databricks, SQL, Python, Java.
Responsibilities
Design automated data quality validation frameworks including rules engines and anomaly detection; Build and maintain automated test procedures for data ingestion and transformation; Investigate data quality defects and drive remediation; Collaborate with engineering teams to translate business/compliance rules into technical test plans; Develop and maintain QA automation scripts and dashboards; Conduct data mining and profiling to identify quality risks; Ensure data security processes align with PHI handling and governance requirements.
Seniority
Mid-level, hands-on IC