Data Platform Engineering Lead - Build & Mentor Pipelines

Reflection AI Ltd

New York (NY)

On-site

USD 180,000 - 300,000

Full time

14 days+
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Benefits offered by this job

Top-tier compensation
Stock options
Health & wellness
Meals provided
Parental leave
Unlimited PTO
Visa sponsorship
Team building

Job summary

Reflection AI Ltd is building the trusted data backbone for open-weight AI systems. We are seeking a front-line technical leader to build, mentor, and grow the Data Platform team of ~10 engineers, guiding its technical direction while remaining hands-on.

You will work with research, training, and production teams to enable high-velocity experimentation on a unified data layer, establish data quality, lineage, and governance, and keep cost and performance predictable through guardrails and

Qualifications

  • 8+ years of engineering experience with production-grade pipelines at large scale.
  • Experience as a staff/principal-level individual contributor before moving into leadership.
  • Experience growing a team and leading 5–10 engineers.
  • Deep experience across ingestion/orchestration, storage/processing engines, and data quality/reproducibility systems.

Responsibilities

  • Build, mentor, and grow a data platform team of ~10 engineers.
  • Define technical direction for ingestion, orchestration, compute, storage, and pipelines.
  • Collaborate with research, training, and production teams to enable high-velocity experimentation.
  • Establish data quality, lineage, and governance signals.
  • Manage cost and performance through guardrails and tuning.
  • Stay hands-on with design reviews and architecture decisions.

Skills

Team leadership
Data engineering
Mentoring
Communication

Tools

Spark
Flink
Airflow
Dagster
Kafka
BigQuery
Snowflake

Job description

Reflection AI Ltd is building the trusted data backbone for open-weight AI systems. We are seeking a front-line technical leader to build, mentor, and grow the Data Platform team of ~10 engineers, guiding its technical direction while remaining hands-on.

You will work with research, training, and production teams to enable high-velocity experimentation on a unified data layer, establish data quality, lineage, and governance, and keep cost and performance predictable through guardrails and

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