Los Angeles, CA30+ days ago
You have deep technical expertise in one or more aspects of data engineering, such as: • Media or other large-scale, multi‑modal asset processing pipelines • Building ML- and experimentation-ready data products • Data warehousing and dimensional/semantic data modeling • Batch and streaming data processing • Media or other large-scale, multi‑modal asset processing pipelines • Building ML- and experimentation-ready data products You're comfortable with a collection of Big Data and cloud-based tech (e.g., S3 or similar object storage, Spark or other distributed processing frameworks, modern data warehouses, workflow orchestration), and are able to make sound architecture and infrastructure tradeoffs. You are comfortable owning the technical quality of both: Analytics-focused data engineering (ETL/ELT, modeling, warehousing, data quality), and ML-focused data engineering (feature pipelines, media and multi‑modal data preparation, training/serving data sets), even if you are not writing production code every day.