Senior Software Engineer (Data & AI Solutions)

Natera is a global leader in cell-free DNA testing, dedicated to oncology, women’s health, and organ health. They are seeking an experienced Senior Software Engineer to design and build data products that support genomics research and translational science, leveraging skills in data engineering and bioinformatics.

Responsibilities:

• Design, build, and maintain the data products that support R&D, analytics, Lab and scientific workflows, from initial design through deployment and iterations
• Build and maintain data pipelines for large and complex datasets, from raw inputs through derived and analysis-ready datasets
• Apply domain knowledge in genetics and bioinformatics to design data models, schemas, and abstractions that align with real research patterns and downstream analysis needs
• Design and enforce de-identification and privacy-preserving architectures that meet HIPAA and related regulatory requirements while remaining usable for research
• Design scalable data models to power analytics, reporting, and downstream applications. Maintain high standards of data quality, accuracy, lineage, and observability across data pipelines
• Partner closely with R&D scientists, bioinformatics teams, and software engineers to translate research needs into well-structured, reusable data assets
• Optimize storage, retrieval, and lifecycle management for large scientific files (E.g. sequencing data, intermediate artifacts, derived datasets)
• 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

Requirements:

• Bachelor's or Master's degree in computer science or bioinformatics 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)
• Strong background in bioinformatics, genomics, or computational biology (required). Understands key genomics and bioinformatics data formats, such as BAM, VCF, FASTQ, common compression techniques for these file formats, and their storage, delivery, and management needs
• Demonstrated experience supporting scientific R&D, Lab workflows and research teams with production-grade data systems
• 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
• 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
• Exposure to vector databases, embeddings, semantic search, or RAG-based architectures is a plus