Data QA Engineer

abacusinsights

Nepal

Posted Jul 21, 2026

Other
On-site
TechOps

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Job description

About Us

Abacus Insights is transforming how data works for health plans. Our mission is simple: make healthcare data usable, so the people responsible for care and cost decisions can act faster, with confidence.

We help health plans break down data silos to create a single, trusted data foundation. That foundation powers better decisions—so plans can improve outcomes, reduce waste, and deliver better experiences for members and providers alike. Backed by $100M from top investors, we’re tackling big challenges in an industry that’s ready for change. Our platform enables GenAI use cases by delivering clean, connected, and reliable healthcare data to support automation, prioritization, and decision workflows—and it’s why we are leading the way.

Our innovation begins with people. We are bold, curious, and collaborative—because the best ideas come from working together. We embrace the thoughtful use of AI and automation to drive innovation and efficiency, and we look for individuals who are curious and adaptable—those excited to leverage emerging technologies to enhance how we work—while keeping human insight, connection, and our clients at the center of every decision.

Ready to make an impact? Join us and let’s build the future together.

About the Role

As a Data Quality Engineer at Abacus Insights, you will ensure the accuracy, reliability, and compliance of healthcare data powering our cloud‑native data management platform. This role requires specialized knowledge in data engineering, data quality frameworks, and healthcare data domains. You will design automated testing procedures, build data validation solutions, and collaborate with engineering and product teams to maintain high‑trust, high‑quality datasets for health plan clients. Your work directly supports regulatory and operational integrity across Abacus’s data ecosystem.

Your day to day

Design, develop, and maintain automated data quality validation frameworks, including rules engines, anomaly detection, and monitoring for completeness, conformity, integrity, and timeliness
Build and maintain automated test procedures for healthcare data ingestion, transformation, and downstream applications
Investigate data quality defects, analyze root causes, and drive remediation recommendations
Review and refine data quality strategies and contribute to standardized quality processes across pipelines
Collaborate with Engineering, Project Management, Operations, and Connector Engineering teams to translate business and compliance rules into technical test plans, functional specifications, and validation logic
Review software and data defect reports, highlight problem areas, and document reproducible issues
Develop and maintain QA automation scripts and dashboards using SQL, Python, Java, and cloud‑native tools
Participate in system verification protocol design and cross‑functional design meetings
Conduct data mining and profiling on client‑specific and healthcare datasets to identify quality risks and gaps
Produce documentation including test plans, validation criteria, rule catalogs, and QA runbooks
Support ongoing monitoring of data quality and respond to internal and external data inquiries
Ensure data security and quality processes align with PHI handling, HIPAA, SOC 2, and Abacus governance requirements

What you bring to the team

Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Analytics, or related technical field
3–5+ years of experience in Data Quality, Data Engineering, or QA roles in healthcare technology or payer/provider environments
Strong SQL expertise, including data manipulation, data validation, and profiling at scale
Experience working with healthcare data types such as enrollment, medical claims, pharmacy claims, provider data, or non‑traditional health and wellness datasets
Hands‑on experience with automation scripting in Python or Java
Postman experience, specifically hands-on API testing experience.
Experience with cloud computing environments such as AWS (S3, EC2, SSM, Athena) and Databricks
Experience with data integration workflows, ETL/ELT pipelines, data mapping, and QA testing protocols
Experience building automated QA applications, dashboards, or custom rule frameworks
Ability to analyze complex datasets, identify quality issues, and generate actionable insights
Excellent communication skills with the ability to work cross‑functionally and independently
Strong organizational skills to manage multiple priorities and deadlines

What we would like to see, but not required

Exposure to Delta Lake, Spark, Airflow, dbt, or event‑driven architectures
Knowledge of schema evolution management (Parquet, Avro, ORC, JSON)
Experience with advanced data quality lifecycle management 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

What you’ll get in return

Competitive Leave & Benefits
Comprehensive health coverage
Equity for every employee – share in our success
Growth-focused environment – your development matters here

Work Arrangements

Standard hours: 9 hours/day, 5 days/week
Location: On-site
Work time: 10 AM - 7 PM (Specific working hours may vary based on business needs.)

Our Commitment as an Equal Opportunity Employer

As a mission-led technology company helping to drive better healthcare outcomes, Abacus Insights believes that the best innovation and value we can bring to our customers comes from diverse ideas, thoughts, experiences, and perspectives. Therefore, we dedicate resources to building diverse teams and providing equal employment opportunities to all applicants. Abacus prohibits discrimination and harassment regarding race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

At the heart of who we are is a commitment to continuously and intentionally building an inclusive culture—one that empowers every team member across the globe to do their best work and bring their authentic selves. We carry that same commitment into our hiring process, aiming to create an interview experience where you feel comfortable and confident showcasing your strengths. If there’s anything we can do to support that—big or small—please let us know.

AI Use in Recruitment

We use AI-powered tools throughout our recruitment process. This includes Greenhouse's Real Talent Matching Technology, which helps prioritize applications based on job-related criteria, as well as additional AI tools used to support sourcing, interview preparation, and other recruiting tasks. We do not remove the human element—our recruiters and hiring teams review all applications and make all decisions related to candidate progression and hiring, regardless of which tools are used to support that process.

By applying, you acknowledge that we will collect and process your personal information for recruiting purposes in accordance with applicable data protection laws. Please review our Applicant Privacy Notice for more information, including your rights.