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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