Senior Data QA Engineer

Software EngineeringRemoteposted 7w ago

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 Senior Data Quality Engineer at Abacus Insights, you will own the accuracy, reliability, and compliance of healthcare data powering our cloud-native data management platform. This role requires deep expertise in data engineering, data quality architecture, and healthcare data domains. You will architect automated testing frameworks, lead data validation strategy, and partner with Engineering and Product leadership to maintain high-trust, high-quality datasets for health plan clients at scale. You will also mentor junior QA engineers and help shape the broader data quality practice across Abacus's data ecosystem, directly supporting regulatory and operational integrity.

Your day to day

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

What you bring to the team

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.

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
Home office setup allowance – one-time support to get you started
Monthly cell phone allowance – stay connected with ease

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.