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Engineering Manager, Data Platform
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Engineering Manager, Data Platform (AI/Data Infrastructure): Building and operating unified data systems and pipelines for open-weight AI research, training, and production with an accent on scalable ingestion, orchestration, storage, and reproducibility. Focus on growing a team of data platform engineers, designing reliable lakehouse infrastructure, and controlling data quality, lineage, cost, and performance at tens of terabytes to petabytes per day.
Location: On-site in San Francisco, New York, or London
Company
is a research lab building open-weight AI models and the data infrastructure that supports their research, training, and production environments.
What you will do
- Build, mentor, and grow a team of approximately 10 data platform engineers.
- Set the technical direction for batch and streaming ingestion, orchestration, scalable compute, and storage.
- Develop reproducible pipelines with versioning, backfills, and isolated execution environments.
- Partner with research, training, and production teams to support high-velocity experimentation on a unified data layer.
- Establish data quality, lineage, governance, cost, and performance controls.
- Stay hands-on through design reviews, architecture decisions, and critical code contributions.
Requirements
- 8+ years of engineering experience with a strong data engineering foundation.
- Experience shipping and owning production-grade pipelines processing tens of terabytes to petabytes daily.
- Previous staff- or principal-level individual contributor experience before moving into engineering leadership.
- Experience managing and growing a team of approximately 5–10 engineers, or clear readiness to build one quickly.
- Deep expertise in ingestion and orchestration, storage and processing engines, or data quality, lineage, and reproducibility systems, with working breadth across the other areas.
- Strong communication skills and the ability to work across research and infrastructure teams in a fast-paced environment.
Nice to have
- Experience building new data systems from zero rather than maintaining legacy platforms.
- Experience with Spark, Flink, Beam, Airflow, Dagster, Kafka, Pub/Sub, Parquet, Iceberg, Delta Lake, BigQuery, Snowflake, Great Expectations, and SLA-driven pipelines.
Culture & Benefits
- Salary and equity are structured to recognize and retain talent globally.
- Stock options for employees.
- Comprehensive medical, dental, vision, and life insurance, plus an annual wellness allowance.
- Daily lunch and dinner in the office.
- 22 weeks of paid parental leave for birthing and non-birthing parents.
- Unlimited paid time off in the U.S. and 30 vacation days in the U.K.; visa sponsorship and long-term immigration support are available where applicable.
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