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Jobs(30,668)/QA Engineer Role(194)/Abacus Insights (9) - Senior Data QA Engineer
Abacus Insights

Abacus Insights - Senior Data QA Engineer

Remote - US+ Equity1w ago
RemoteSeniorNACloud ComputingData AnalyticsQA EngineerSenior Data EngineerData QualityReportingSQLJavaAWSPythonDatabricksAirflowdbtGitTerraformMentoringDocumentationGovernance

Requirements

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Analytics, or related technical field, or equivalent work experience. • 6–8+ years of experience in Data Quality Engineering and Data Engineering, with significant experience in healthcare technology or payer/provider environments • Expert-level SQL skills, including complex data manipulation, validation, and profiling at scale • Proven ability to lead data quality projects end-to-end. • Deep experience working with healthcare data types such as enrollment, medical claims, pharmacy claims, provider data, or non-traditional health and wellness datasets • Strong hands-on automation scripting expertise in Python or Java, with a track record of building reusable frameworks • Proven experience with cloud computing environments such as AWS (S3, EC2, SSM, Athena) and Databricks in production-scale settings • Demonstrated experience designing data integration workflows, ETL/ELT pipelines, data mapping strategy, and enterprise QA testing protocols • Track record of building and scaling automated QA applications, dashboards, or custom rule frameworks from the ground up • Proven ability to analyze complex, large-scale datasets, identify systemic quality issues, and drive actionable, measurable improvements • Experience mentoring engineers and influencing technical direction across teams • Excellent communication skills, with the ability to work cross-functionally, influence stakeholders, and operate independently with minimal oversight • Strong organizational and prioritization skills in a fast-paced, multi-project environment • What we would like to see, but not required • Deep exposure to Delta Lake, Spark, Airflow, dbt, or event-driven architectures • Advanced knowledge of schema evolution management (Parquet, Avro, ORC, JSON) • Experience leading data quality lifecycle management initiatives in large-scale cloud systems • Familiarity with Terraform, DevOps pipelines, CI/CD workflows, Git-based version control • Background in software debugging, system testing methodologies, or performance testing at an architectural level • Compensation: Compensation for this role is based on experience, skills, and location, and includes base salary plus eligibility for performance bonuses and equity grants.

Responsibilities

• Architect, build, and maintain enterprise-scale automated data quality validation frameworks, including rules engines, anomaly detection, and monitoring for completeness, conformity, integrity, and timeliness • Lead design and implementation of automated test strategies for complex healthcare data ingestion, transformation, and downstream application pipelines • Drive root cause analysis on high-impact data quality defects, own remediation strategy, and prevent recurrence through systemic process improvements • Define and evolve data quality strategy, standards, and best practices across pipelines, influencing tooling and process decisions org-wide • Partner directly with Engineering, Product, Project Management, Operations, and Connector Engineering leadership to translate business and compliance requirements into technical test plans, functional specifications, and validation logic • Lead review of software and data defect reports, identify systemic problem areas, and establish standards for reproducible issue documentation • Design and maintain advanced QA automation frameworks and dashboards using SQL, Python, Java, and cloud-native tooling • Lead system verification protocol design and represent QA in cross-functional architecture and design discussions • Conduct advanced data mining and profiling on client-specific and healthcare datasets to proactively surface quality risks at scale • Own documentation strategy including test plans, validation criteria, rule catalogs, and QA runbooks • Mentor and provide technical guidance to junior and mid-level QA engineers • Serve as an escalation point for internal and external data quality inquiries • Ensure data security and quality processes align with PHI handling, HIPAA, SOC 2, and Abacus governance requirements, and help evolve governance standards as the platform scales

Benefits

• What you’ll get in return • Unlimited paid time off – recharge when you need it • Work from anywhere – flexibility to fit your life • Comprehensive health coverage – multiple plan options to choose from • Equity for every employee – share in our success • Growth-focused environment – your development matters here • Monthly cell phone allowance – stay connected with ease

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