• Lead the rebuild of our data stack with a modern Snowflake data lakehouse, architected for scale and performance on AWS • Design and implement best-in-class AWS data infrastructure using Terraform for provisioning, configuration, and automation • Influence data architecture, tooling choices, and long-term strategy, ensuring alignment with business and technology needs and growth plans • Build and optimize scalable ETL/ELT pipelines with AWS services, Python, and Airflow • Establish and enforce rigorous standards for data quality, observability, and governance, including access control, lineage, and compliance requirements • Prepare and evolve the data platform to support advanced analytics, AI, and machine learning use cases • Collaborate closely with Product, Engineering, and Customer Success to deliver reliable, trusted data for analytics and reporting

• Levantamento, construção de processos de integração de dados, data pipelines e dashboards; • Integração de dados com as soluções dos parceiros, através de coleta e armazenamento das informações dos clientes, transformação e carga nos data stores das soluções; • Implantação, gerenciamento e monitoramento dos fluxos de integração de dados; • Desenvolvimento de relatórios operacionais, dashboards e indicadores de desempenho;

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We're looking for an engineer to own Runway's internal exploratory data analysis (EDA) and evaluation platform used daily by our ML research, design, product, and creative teams. This is a high-impact role where you'll directly accelerate research velocity and enable better decision-making across the company. This platform helps researchers query large-scale datasets, run evaluations on model outputs, and analyze results - all through an intuitive interface. As the owner, you'll be responsible for the full product experience: - Database query optimization and infrastructure management - Building user-facing features that make complex ML workflows accessible to non-engineers A peek at our technical stack: - API endpoints for real-time collaboration and media asset management written in TypeScript, running in ECS containers on AWS Fargate - Leveraging multiple AWS-native components, such as S3, CloudFront, Lambda, Kinesis, and SQS - Inference backend written in Python (PyTorch, TorchScript), deployed across multiple clusters/cloud providers - Using Kubernetes for container orchestration, and k8s-native components such as Flyte, Kueue, and Kyverno for efficient job orchestration - Investing in Prometheus and Grafana for monitoring, and Terraform to manage infrastructure Qualifications - 4+ years of industry experience in a backend focused software engineering role - Strong experience in at least 2 of 3 areas (platform/infrastructure, ML domain knowledge, frontend/product engineering) with eagerness to learn the third: - Platform/infrastructure: experience with vector databases, cloud primitives (i.e. SQS, ECR, Kinesis) and container orchestration (Kubernetes, ECS) - ML domain knowledge: Understanding of ML workflows, model training, evaluation, testing, dataset management, feature engineering, or research tooling - Product engineering: Ability to build clean, intuitive user experiences with product thinking and user empathy (TypeScript/React experience is a plus) - Comfortable setting up and maintaining production infrastructure and services - Self-starter who can navigate ambiguity and make pragmatic technical decisions - Humility and open-mindedness; at Runway we love to learn from one another Requirements - Ability to build tools people love to use Benefits - Salary range: $240,000 - $290,000 - Commitment to creating a space where employees can bring their full selves to work and have equal opportunity to succeed Company Description Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage, and industry, and salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. We're excited to be recognized as a best place to work: - Crain's - InHerSight - BuiltIn NYC - INC

• Design, develop, and maintain scalable ETL/ELT pipelines using Python and SQL. • Ensure high data quality, integrity, and availability for downstream analytics and pharmacy workflows. • Collaborate with data scientists, analysts, and pharmacy domain experts to understand requirements. • Troubleshoot and optimize data models and pipelines for performance and reliability. • Work in a cloud environment to support modern, scalable pharmacy technology infrastructure. • Play a critical role in enabling pharmacy data flows and ensuring end-to-end software reliability.