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Runway Logo Runway · IT - Software Development

Member of Technical Staff, Data Infrastructure

240000.00 - 290000.00 USD / Year · Job Posted January 20, 2026
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Job Description

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.

Job Responsibility

  • 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

Requirements

  • 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

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
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