Senior Data QA Engineer
Abacus Insights22 days ago
Responsibilities
- Architect, build, and maintain automated data quality validation frameworks with rules engines, anomaly detection, and monitoring.
- Lead automated test strategy for healthcare data ingestion, transformation, and downstream application pipelines.
- Drive root cause analysis, remediation strategy, and recurrence prevention for high-impact data quality defects.
- Define data quality standards, best practices, validation logic, and tooling decisions across the organization.
- Partner with Engineering, Product, Project Management, Operations, and Connector Engineering leadership on technical test plans and specifications.
- Design QA automation frameworks, system verification protocols, dashboards, test plans, validation criteria, rule catalogs, and runbooks.
- Conduct data mining and profiling on healthcare datasets to identify quality risks at scale.
- Mentor junior and mid-level QA engineers and provide technical guidance across teams.
- Support data security, PHI handling, HIPAA, SOC 2, and governance requirements.
Requirements
- Bachelor's or master's degree in Computer Science, Information Systems, Data Analytics, or a related technical field, or equivalent work experience.
- 6–8+ years of experience in Data Quality Engineering and Data Engineering, including significant healthcare technology or payer/provider experience.
- Expert SQL skills for complex data manipulation, validation, and profiling at scale.
- Hands-on Python or Java automation scripting experience building reusable frameworks.
- Experience with healthcare data such as enrollment, medical claims, pharmacy claims, provider data, or health and wellness datasets.
- Production-scale experience with AWS services including S3, EC2, SSM, and Athena, plus Databricks.
- Experience designing data integration workflows, ETL/ELT pipelines, data mapping strategies, and enterprise QA testing protocols.
- Experience building and scaling automated QA applications, dashboards, or custom rule frameworks.
- Ability to analyze large-scale datasets, identify systemic quality issues, and drive measurable improvements.
- Experience mentoring engineers and influencing technical direction across teams.
- Preferred exposure to Delta Lake, Spark, Airflow, dbt, event-driven architectures, schema evolution, Parquet, Avro, ORC, JSON, Terraform, DevOps pipelines, Git-based version control, software debugging, system testing, or performance testing.
Benefits
- Unlimited paid time off.
- Work from anywhere.
- Comprehensive health coverage with multiple plan options.
- Equity for every employee and eligibility for performance bonuses and equity grants.
- Growth-focused development environment.
- One-time home office setup allowance.
- Monthly cell phone allowance.
Categories
Data EngineeringTesting