Manager, Data Engineering

About the position

Natera is a global leader in cell-free DNA testing, supporting oncology, women's health, and organ health. Our goal in R&D Operations Data Science is to support R&D activities at Natera through data analytics and software tool development to optimize workflows and processes. As a Data Engineering Manager on the team, you will lead the design, development, and deployment of scalable data infrastructure, backend services, and software tools that enhance operational efficiency in R&D. Your role will focus on implementing new processes, optimizing data workflows, and developing software solutions to support R&D initiatives. You will work independently and cross-functionally, collaborating with R&D, data science, software engineering, and DevOps teams to build and maintain high-performance data pipelines, APIs, and cloud-based solutions. Additionally, you will manage a team of engineers, ensuring best practices in data engineering, cloud infrastructure, DevOps, and frontend integration.

Responsibilities

• Lead the design and implementation of scalable data pipelines for ETL, data ingestion, and data transformation.
• Develop and deploy REST APIs and microservices using FastAPI (or similar Python frameworks).
• Implement and manage high-performance caching layers using Redis and Elasticsearch.
• Oversee data migration, data replication, and integration across multiple systems.
• Ensure data quality, governance, and reliability in engineering workflows.
• Design and maintain CI/CD pipelines using GitLab CI/CD for automated deployments.
• Deploy and manage services on AWS cloud infrastructure (EC2, Fargate, Lambda, S3, RDS, etc.).
• Implement containerization and orchestration using Docker and Kubernetes.
• Monitor and optimize system performance, logging, and alerting for production workloads.
• Implement strategic cost optimization initiatives of cloud infrastructure.
• Develop custom software tools to optimize R&D workflows and process automation.
• Work with stakeholders to identify pain points and design engineering solutions that improve efficiency.
• Implement data visualization tools and dashboards to improve operational insights.
• Design and implement user-friendly data interfaces for internal R&D teams.
• Manage and mentor a team of data engineers.
• Drive best practices for code quality, testing, and documentation.
• Identify and implement new tools and technologies to improve data workflows and software development processes.
• Collaborate with cross-functional teams to align engineering efforts with R&D objectives.

Requirements

• 5+ years of experience in data engineering, backend development, and DevOps.
• Strong programming skills in Python.
• Knowledge of data pipelines, ETL processes, and database management.
• Expertise in microservices and REST API development (FastAPI preferred).
• Strong experience with AWS services (EC2, Fargate, Lambda, S3, RDS, etc.).
• Proficiency in CI/CD automation using GitLab CI/CD.
• Experience with containerization (Docker, Kubernetes).
• Familiarity with infrastructure-as-code (Terraform, CloudFormation).
• Familiarity with React.js for frontend integration.
• Excellent problem-solving and leadership skills.

Nice-to-haves

• Experience with streaming data processing (Kafka, Spark, etc.).
• Experience with workflow orchestration tools (Apache Airflow).
• Knowledge of data governance and security best practices.
• Hands-on experience with Redis, Elasticsearch, and data caching strategies.

Benefits

• Comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents.
• Free testing for employees and their immediate families.
• Fertility care benefits.
• Pregnancy and baby bonding leave.
• 401k benefits.
• Commuter benefits.
• Generous employee referral program.