Senior Software Engineer, Data & AI Solutions - Billing

Requirements

• Experience in healthcare, pharma, diagnostics, or other regulated industries
• Experience with cloud data platforms (Snowflake or AWS tech stack)
• Experience supporting analytics tools and BI platforms/data visualization tools like Power BI, Qlik Sense, Tableau or similar
• Experience with dbt, Airflow, or similar modern data stack technologies
• Strong problem-solving and analytical thinking, ability to work cross-functionally with technical and non-technical stakeholders
• The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of exper

Benefits

Additional Information

POSITION SUMMARY: Natera is seeking an experienced Senior Software Engineer with modern data engineering and AI-enabled development skills with deep expertise in healthcare or biotech data ecosystems to design, build, and maintain data products supporting patient, provider, insurance, billing, and customer support operations. This role will partner closely with analytics, product, clinical, and business teams to ensure high-quality, compliant, and reliable data pipelines that drive reporting, analytics, and operational decision-making. The ideal candidate combines strong data engineering skills with a computer science background and hands-on experience integrating complex healthcare systems, billing systems, clearinghouses, and payer systems and the ability to work independently in fast moving Customer and Billing domains. In this role, you will develop enterprise-grade data products that power internal business functions (Customer experience, Billing, LabOps and Sales) in tracking performance, measuring outcomes, and making informed operational and strategic decisions. You will also be comfortable moving quickly to prototype novel data products while ensuring solutions evolve into robust, compliant, and scalable platforms. PRIMARY RESPONSIBILITIES: Design, build, and maintain the data products of the CX(Customer Experience) and Billing domains, from initial design through deployment and iterations Build integrated data pipelines and models across patient, provider, payer, claims, billing, and revenue cycle domains to enable a comprehensive 360° view Design and optimize scalable ETL/ELT pipelines to ingest, process, and integrate structured and semi-structured data from internal and external sources. Design scalable data models to power analytics, reporting, and downstream applications. Maintain high standards of data quality, accuracy, lineage, and observability across data pipelines. Apply best practices for data security, privacy, and compliance (HIPAA, PHI handling) Drive rapid prototyping efforts to support exploratory, proof-of-concepts, and early-stage initiatives, while guiding the transition to production-grade systems. Implement best practices for data quality, validation, lineage, observability, and reproducibility to enable a trusted 360° view. Collaborate with product managers and domain experts to translate requirements into technical solutions Establish golden paths (templates, examples, docs) and contribute to shared data product catalogs, patterns, and best practices used by other engineers Provide technical guidance and mentorship to mid-level engineers Required Qualifications Bachelor's or Master's degree in computer science or engineering with healthcare or biotech data domain experience preferred 8+ years of experience in data engineering, designing and maintaining data pipelines and cloud data architectures (e.g, Snowflake, AWS, etc) Deep understanding of healthcare data domains including Patient, Provider, Payer, Insurance, Claims, Billing, and Customer Operations processes Strong proficiency in Python, SQL, and distributed processing frameworks (Spark or equivalent) Experience with modern orchestration tools (Airflow, dbt, Dagster) Experience leveraging AI-assisted development tools (e.g., LLM copilots) to accelerate data solution development Familiarity with building data products that support analytics, ML, or AI applications Strong data modeling expertise (dimensional, normalized, healthcare-specific schemas) Experience implementing CI/CD for data pipelines and IaC (Terraform, CloudFormation); Knowledge of data observability, testing, and data quality frameworks Demonstrated ownership of production-grade data systems and end-to-end pipeline lifecycle Ability to evaluate emerging data and AI technologies and recommend scalable solutions Exposure to vector databases, embeddings, semantic search, or RAG-based architectures is a plus Proven ability to operate effectively in fast-paced environments, balancing speed, rigor, and compliance Strong written and verbal communication skills with ability to collaborate across engineering, analytics, and business stakeholders Experience working with healthcare, life sciences, or other highly regulated data, including hands-on HIPAA compliance.

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