Data Platform Engineering Lead: Build & Scale Pipelines

Reflection; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Stock options

Health & wellness

Meals in office

Parental leave

Unlimited PTO

Job summary

Reflection is building the trusted data backbone for the world's most capable open-weight AI systems. We seek a front-line technical leader to build, mentor, and grow this team, guiding its technical direction while staying hands-on to multiply credibility through the team.

You will work closely with research to enable high-velocity experimentation, establish data quality and governance signals, and keep cost and performance predictable across the data estate.

Qualifications

• 8+ years of engineering experience with a strong data engineering foundation.
• Staff/Principal-level individual contributor before moving into leadership.
• Managed and grown a team of 5–10 engineers or demonstrated leadership readiness.
• Deep expertise in ingestion & orchestration at scale, storage/processing engines, or data quality/lineage/reproducibility.

Responsibilities

• Build, mentor, and grow a team of ~10 data platform engineers with coaching and hiring.
• Guide technical direction across ingestion, orchestration patterns for batch/streaming workloads, scalable compute/storage foundations.
• Collaborate with research, training, and production teams to enable high-velocity experimentation on a unified data layer.
• Establish data quality, lineage, and governance signals for confident production decisions.
• Keep cost and performance predictable through guardrails, budgets, and continuous system tuning.
• Stay hands-on with design reviews, architecture decisions, and code where it matters most.

Job description

Reflection is building the trusted data backbone for the world's most capable open-weight AI systems. We seek a front-line technical leader to build, mentor, and grow this team, guiding its technical direction while staying hands-on to multiply credibility through the team.

You will work closely with research to enable high-velocity experimentation, establish data quality and governance signals, and keep cost and performance predictable across the data estate.