JOB-1652
Our client is a data-product company whose core asset is a very large dataset describing people, and it is building AI access layers on top of it. It is hiring a seasoned data engineer to operate and grow the data pipelines, storage tiers and normalization systems underneath both the data product and the AI platform.
What you’ll own
- Handle ingestion, modeling and transformation for a large people-data product, refining its attributes, features and the pipelines that produce them
- Grow integrations with customers’ own revenue-team platforms, supporting a data footprint already in the multi-terabyte range
- Work alongside data scientists to productionize complex pipelines, scale them and keep the data trustworthy
- Open up AI and agent-style access, from retrieval APIs that accept plain-language questions to orchestration of structured data
- Join tactical teams whose data products help unlock major customer contracts
- Tools include Snowflake, an S3 lakehouse, dbt, Dagster and AWS
What you bring
- Three or more years building and scaling data infrastructure
- End-to-end ownership of ingestion for large, messy, multi-source data, including connectors, deduplication, schema changes and reruns
- Experience building the pipelines that feed analytics or machine learning, as the data engineer rather than the modeler
- Strong command of orchestration tools such as Airflow, Dagster, Prefect, dbt or SQLMesh
- Background at a venture-backed startup or a company with a high talent bar
- Infrastructure for AI applications such as retrieval APIs is a plus
On-site in New York, NY. Visa transfers considered.
