Member of Technical Staff – Data Platform

About the role

Join Reflection's Foundations team to build and operate the core data systems that power research, training, and production AI workloads. You will design scalable ingestion and orchestration patterns for both batch and streaming workloads, enabling high‑velocity experimentation and reliable model development.

Key responsibilities

• Design and implement reliable, scalable ingestion pipelines using Spark, Flink, Beam, Airflow, Dagster, Kafka, and PubSub.
• Develop storage foundations (Parquet, Iceberg, Delta Lake) and compute platforms (BigQuery, Snowflake) to support large‑scale data processing.
• Ensure reproducible pipelines through versioning, backfills, and isolated execution environments.
• Provide data quality, lineage, and governance signals using metadata systems and Great Expectations.
• Maintain cost and performance guardrails, budgets, and continuous system tuning.

Required profile

• Strong data engineering background with experience shipping production‑grade pipelines at scale.
• Proven ability to design end‑to‑end data systems handling large batch and streaming workloads.
• Comfortable debugging complex pipeline failures and optimizing for cost, performance, and data quality.
• Thrives in a high‑agency, fast‑paced environment and enjoys building new systems from zero to one.

Required skills

• Spark, Flink, Beam, Airflow, Dagster, Kafka, PubSub
• Parquet, Iceberg, Delta Lake, BigQuery, Snowflake
• Great Expectations, metadata management, data lineage tools

What we offer

• Top‑tier compensation with salary and equity.
• Stock options for all contributors.
• Comprehensive health, dental, vision, and life coverage plus an annual wellness allowance.
• Daily lunch and dinner provided on‑site.
• Unlimited paid time off in the U.S. and generous parental leave.
• Visa sponsorship and support for long‑term immigration pathways.