Abacus Insights

healthcare

DataQAEngineer

Kathmandu, Bagmati, Nepal Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Data QA Engineer at Abacus Insights. Skills: Data QA, Data Engineering QA, SQL, Python, PySpark, Databricks, AWS. Review mapping specifications to identify business requirement gaps and estimated QA efforts. Design ETL test scenarios and test cases”

What You'll Achieve.

make healthcare data usable; create a single, trusted data foundation; improve outcomes; reduce waste; deliver better experiences for members and providers alike; support automation, prioritization, and decision workflows

Industry & Context.

healthcare
Problems you'll solve

analyze large datasets; identify inconsistencies; validate business logic

Eligibility Requirements

Onsite, Shift: 10 AM – 7 PM local time

What They're Looking For.

Must Have

2+ years of hands‑on experience in Data QA or Data Engineering, expertise in SQL, including complex queries, joins, aggregations, performance optimization, and data validation, Working knowledge of Python for data analysis, synthetic data creation, and automation of QA processes, Proven ability to analyze large datasets, identify inconsistencies, and validate business logic, Solid understanding of QA methodologies with experience designing test cases for data‑centric systems, Experience with PySpark, Databricks, and AWS services such as Redshift, S3

Nice to Have

Experience with BigQuery, Snowflake, and ETL test automation, Hands‑on API testing experience, Healthcare domain knowledge, including HEDIS quality measures

What You'll Do.

Review mapping specifications to identify business requirement gaps and estimated QA efforts

Design ETL test scenarios and test cases

Validate input file layouts and parsers

Write source-to-target SQL queries for data validation and user acceptance criteria

Automate data validation using PySpark and Databricks

Execute testing using synthetic data resembling real‑time production scenarios

Implement and configure data pipelines that ingest and do the ETL and process diverse sources of data

Build large batch processing and streaming systems

Drive the evolution of the product and team

Bring experience to best practices as we build out new components of the platform

How You'll Work.

Team & Collaboration

guiding voice on a critical feature delivery team; worked in Agile methodology; coordinated onsite–offshore teams; collaborative

Process & Methodology

Agile methodology, tracked QA activities in Jira/test management tools

Full 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: Our TechOps team is looking to bring on an experienced Data QA Engineer. If you are interested in being a guiding voice on a critical feature delivery team, this position is for you. The team is responsible for implementing and configuring the data pipelines that ingest and do the ETL and process diverse sources of data. This includes building large batch processing and streaming systems. You will be exposed to every area of our platform and AWS services (Serverless – Lambda, EMR – Hadoop/Spark, EKS – Kubernetes, etc.) but even more so, help drive the evolution of the product and team as we continue to grow rapidly. We believe heavily in architecture evolution, and you will bring your experience to best practices as we

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