RunwayMember of Technical Staff, Data Infrastructure
About the role
We're looking for a Data Engineer to build and scale the data infrastructure that powers Runway's AI research and business intelligence. You'll own critical data pipelines spanning production databases, analytics warehouses, and large-scale ML training datasets. This role sits at the intersection of data engineering, ML infrastructure, and analytics—you'll enable both world-class research and data-driven business decisions.
You'll work on challenging problems at scale: managing billions of rows of multimodal training data, building CDC streams from production systems, optimizing vector databases for ML workflows, and creating the foundational data layer that the entire company relies on.
A peek at our technical stack
Our data infrastructure spans multiple specialized systems: LanceDB for vector storage and dataset versioning with multimodal training data, ClickHouse as our analytics warehouse receiving CDC streams from production Postgres via AWS Kinesis, and BigQuery for training run logs and evaluation results. We use Ray for large-scale distributed data processing on managed Kubernetes clusters, handling preprocessing, feature generation, and dataset curation at scale.
We're actively building out our data platform—introducing dbt for standardized transformations, improving dataset versioning and data lineage tracking, scaling data sourcing pipelines, and establishing better data quality practices. We use Prometheus and Grafana for monitoring, and Terraform for infrastructure management. This is an opportunity to bring best practices and technical leadership as we mature our data infrastructure to support rapidly growing ML training and research needs.
What you’ll do
- Build and own pipelines for the creation, curation, and processing of large-scale multimodal datasets, including vector database (LanceDB) management and query optimization for ML metadata
- Build and own ETL and CDC streams from Postgres and ClickHouse to analytics warehouses
- Build standardized data transformation layers using dbt to replace ad-hoc SQL queries and create maintainable data models for business analytics
- Manage production databases (Postgres, ClickHouse) and optimize for performance and reliability
What you’ll need
- 4+ years of industry experience in data engineering
- Strong knowledge of Python
- Experience with data quality, deduplication, and cleaning at scale
- Comfortable working with cloud storage (S3) and managing large datasets
- Experience building and maintaining ETL/CDC pipelines at scale
- Strong SQL skills and experience with multiple database systems (Postgres, columnar databases like ClickHouse/Redshift)
- Humility and open mindedness; at Runway we love to learn from one another
Nice to Have
- Experience with one or more frameworks for large-scale data processing (e.g. Spark, Ray, etc) and one or more ML frameworks (e.g. PyTorch, JAX)
- Knowledge of cloud platforms (AWS, GCP, or Azure) and their data service offerings
- Knowledge of data privacy and data security best practices
- Experience with business intelligence and visualization tools (e.g., Looker, Tableau, PowerBI, Metabase, or similar)
- Experience in a high-growth startup environment or similar fast-paced setting
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. In this case, we will communicate any updates in the expected salary range.
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.
Salary range: $240,000-290,000