Head of Data Platform | Frontier AI Research Lab

Oscar Faye; New York (NY); On-site; USD 180,000 - 250,000; Full time

Benefits offered by this job

Health cover

Parental leave

Visa sponsorship

Equity

Flexible time off

Job summary

Oscar Faye AI research lab is seeking a hands-on technical leader to build and run its Data Platform team that underpins research, training and production across ingestion, processing and orchestration.

You will scale a team of about 10 engineers, set the platform's direction, mentor staff, and stay hands-on in design reviews and code where it matters most. This role blends leadership with technical depth in a frontier data stack.

Qualifications

• 10+ years in engineering with a strong data foundation.
• Experience as staff/principal IC before moving to leadership.
• Proven ability to hire and coach a 5–10 person team.
• Deep knowledge across ingestion, orchestration, lakehouse, and data quality.

Responsibilities

• Build and mentor a 10-person data platform team and raise the bar with each hire.
• Set the platform's direction for batch and streaming ingestion, scalable compute, and reproducible pipelines.
• Collaborate with research, training, and production teams to run experiments quickly on a shared data layer.
• Implement data quality, lineage, and governance to enable confident production decisions.
• Manage cost and performance with guardrails and ongoing tuning.

Skills

Data engineering

Leadership

Team management

Production pipelines

Big data

IC track record

Tools

Spark

Flink

Airflow

Dagster

Kafka

Pub/Sub

Parquet

Iceberg

Delta Lake

BigQuery

Snowflake

Great Expectations

Job description

An extremely well-funded AI research lab training frontier foundation models wants a hands-on technical leader to build and run its Data Platform team. This team owns the data backbone behind research, training and production: ingestion, processing and orchestration across the whole data lifecycle.

This is for someone who earned their credibility as a staff or principal engineer and now wants to multiply it through a team. You will set technical direction, hire and coach a team of about 10, and still be in the design reviews and the code where it matters most.

What you will do

• Build, mentor and grow a team of about 10 data platform engineers, and raise the bar with every hire.
• Set the platform's technical direction: batch and streaming ingestion, scalable compute and storage, and reproducible pipelines with versioning, backfills (reprocessing historical data) and isolated execution.
• Work with research, training and production teams so they can run experiments quickly on one shared data layer.
• Put trusted data quality, lineage (where data came from and how it changed) and governance in place, so teams can make production decisions with confidence.
• Keep cost and performance predictable through guardrails, budgets and ongoing tuning.

The stack

Spark, Flink, Beam, Airflow, Dagster, Kafka, Pub/Sub, Parquet, Iceberg, Delta Lake, BigQuery, Snowflake, Great Expectations, lakehouse and warehouse architectures.

What they are looking for

• 10+ years in engineering with a strong data engineering foundation, including owning production pipelines that move tens of terabytes to petabytes a day.
• A track record as a staff or principal-level IC (individual contributor) before moving into leadership.
• Experience managing a team of 5 to 10, or clear readiness to build one quickly while staying technical.
• Depth in at least one of: ingestion and orchestration at scale, lakehouse formats and query engines, or data quality, lineage and reproducibility, with working breadth across the others.
• A history of building new systems from scratch rather than maintaining legacy ones.
• A strong bias to action, and comfort working across research and infrastructure.

What is on offer

• Top-of-market salary plus meaningful equity.
• Comprehensive health cover, generous paid parental leave and flexible time off.
• Visa sponsorship for exceptional candidates.
• A small, talent-dense team where this hire shapes the data foundation of frontier model training.
• Opportunity to be part of a potential generational company