Key Responsibilities :

Data Quality Execution & Support :

- Support data quality assessments across RWD pipelines, source data, harmonized datasets, and client deliverables under guidance from senior team members.

- Assist with investigating data quality issues and escalating findings following defined procedures.

- Analyze data anomalies using SQL queries, dashboards, and pipeline logs to help identify potential root causes.

- Document findings and contribute to remediation actions and follow-up validation.

Quality Checks & Continuous Monitoring :

- Execute and maintain existing data quality checks at ingestion, harmonization, and delivery stages.

- Assist in implementing new quality checks designed by senior team members or engineering.

- Monitor data quality metrics and alerts, flagging deviations from expected thresholds.

- Help identify recurring issues and contribute observations for process improvements.

Cross-Functional & Vendor Support :

- Work with data engineers, analysts, product, and delivery teams to help resolve data quality issues.

- Support validation of external vendor data by checking logic, completeness, and refresh consistency.

- Assist internal teams during data changes, enhancements, or refresh cycles.

- Help respond to data questions from client-facing teams by gathering evidence and documentation.

Communication & Documentation :

- Clearly document data quality investigations, findings, and resolution steps.

- Maintain investigation notes, issue trackers, and supporting documentation.

- Contribute updates to SOPs, data dictionaries, and internal knowledge resources as assigned.

- Assist with internal data release notes related to data product updates.

Required Experience & Education Core Requirements :

- Education : Bachelors degree in Computer Science, Data Science, Information Technology, Public Health, Biostatistics, or a related field.

- Experience : 5+ years of experience in data quality, analytics, or data engineering roles, ideally within healthcare or life sciences.

- Domain Knowledge : Deep understanding of real-world data sources, including claims, EMR/EHR, and lab data, alongside hands-on experience working with large, complex healthcare datasets.

- Technical Proficiency : Proficient SQL skills and experience navigating modern data pipelines and warehouses.

- Key Skills : Proven ability to independently drive investigations from intake through resolution, paired with strong analytical, problem-solving, and detailed documentation skills.

Preferred Skills :

- Knowledge of healthcare data standards, privacy, and compliance requirements (e.g., HIPAA).

- Experience with data analysis and pipeline tools such as Python, R, Airflow, or similar.

- Experience working with Amazon Redshift, DBM, or comparable cloud data warehouse environments.

- Prior experience influencing or designing data quality frameworks, metrics, or controls at scale.