Staff Data Engineer, Foundations & Pipelines

B Capital; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Top-tier compensation

Stock options

Health & wellness

Meals provided

Parental leave

Unlimited vacation

Visa sponsorship

Team off-sites

Job summary

Reflection is a research lab building open models and data foundations to accelerate AI innovation. We design scalable data platforms powering research, training, and production, with a focus on reproducibility, governance, and cost efficiency.

Join a high-impact team that builds from the ground up, partnering across research and infrastructure to enable rapid experimentation and reliable, scalable data workflows.

Qualifications

• Strong data engineering background with production-scale pipelines.
• Experience designing end-to-end data systems for batch and streaming workloads.
• Ability to debug complex pipelines and optimize cost and performance.
• Comfortable working across research and infrastructure boundaries.
• Motivated to build new systems rather than maintain legacy ones.

Responsibilities

• Build and operate core data systems and pipelines powering research, training, and production environments.
• Design and implement reliable ingestion and orchestration for batch and streaming workloads.
• Develop storage and compute foundations enabling reproducible experimentation.
• Drive data quality and governance standards for production decisions.
• Provide unified data layer unifying ingestion, processing, and workflow management.

Skills

Data engineering

Production-grade pipelines

End-to-end data systems

Data quality

Cost optimization

Collaborative communication

System design

Tools

Spark

Flink

Beam

Airflow

Dagster

Kafka

Pub/Sub

BigQuery

Snowflake

Job description

Reflection is a research lab building open models and data foundations to accelerate AI innovation. We design scalable data platforms powering research, training, and production, with a focus on reproducibility, governance, and cost efficiency.

Join a high-impact team that builds from the ground up, partnering across research and infrastructure to enable rapid experimentation and reliable, scalable data workflows.