AI Summary
Lead a team of ~10 data platform engineers to build and operate core data systems for open-weight AI. Guide technical direction for ingestion, processing, and orchestration across the data lifecycle. Requires 8+ years of data engineering experience and proven leadership in a fast-paced environment.
Key Highlights
Build, mentor, and grow a team of ~10 exceptional data platform engineers.
Guide the technical direction across the platform, including ingestion, orchestration, compute, storage, and pipelines.
Enable high-velocity experimentation for research, training, and production teams on a unified data layer.
Key Responsibilities
Build, mentor, and grow a team of ~10 exceptional data platform engineers, hiring, coaching, and raising the bar with every person you add.
Guide the technical direction across the platform: ingestion and orchestration patterns for batch and streaming workloads, scalable compute and storage foundations, and reproducible pipelines with versioning, backfills, and isolated execution environments.
Work closely with research, training, and production teams to enable high-velocity experimentation on a unified data layer.
Establish trusted data quality, lineage, and governance signals so teams can make confident production decisions.
Keep cost and performance predictable through guardrails, budgets, and continuous system tuning.
Stay hands-on: design reviews, architecture decisions, and code where it matters most.
Technical Skills Required
Benefits & Perks
Top-tier compensation
Stock options
Health & wellness
Meals
Paid parental leave
Unlimited paid time off (US)
30 days paid time off (UK)
Sponsorship support
Nice to Have
Spark
Flink
Beam
Airflow
Dagster
Kafka
PubSub
Data lake and warehouse architectures
Parquet
Iceberg
Delta Lake
BigQuery
Snowflake
Lineage systems
Metadata management
Great Expectations
Reproducibility systems
Partitioning strategies
Clustering
Cost optimization
SLA-driven pipelines
Job Description
Our Mission
Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI. Our mission: make intelligence open and accessible to all.
About The Role
Reflection is building the trusted data backbone for the world's most capable open-weight AI systems. The Data Platform team builds and operates the core data systems and pipelines that power our research, training, and production environments unifying ingestion, processing, and orchestration across the entire data lifecycle so every team can move faster.
We're looking for a front-line technical leader to build, mentor, and grow this team. You'll guide its technical direction while staying hands-on this is a role for someone who has earned deep technical credibility as an engineer and now multiplies it through a team. You'll work closely with our research team to understand what high-velocity experimentation actually needs, and turn that into reliable, reproducible, scalable data infrastructure.
What You'll Do
- Build, mentor, and grow a team of ~10 exceptional data platform engineers hiring, coaching, and raising the bar with every person you add.
- Guide the technical direction across the platform: ingestion and orchestration patterns for batch and streaming workloads, scalable compute and storage foundations, and reproducible pipelines with versioning, backfills, and isolated execution environments.
- Work closely with research, training, and production teams to enable high-velocity experimentation on a unified data layer.
- Establish trusted data quality, lineage, and governance signals so teams can make confident production decisions.
- Keep cost and performance predictable through guardrails, budgets, and continuous system tuning.
- Stay hands-on: design reviews, architecture decisions, and code where it matters most.
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- Compute & orchestration: Spark, Flink, Beam, Airflow, Dagster, Kafka, PubSub
- Storage & analytics: data lake and warehouse architectures, Parquet, Iceberg, Delta Lake, BigQuery, Snowflake
- Metadata & data quality: lineage systems, metadata management, Great Expectations, reproducibility systems
- Cost & performance: partitioning strategies, clustering, cost optimization, SLA-driven pipelines
- 8+ years of engineering experience with a strong data engineering foundation — you've shipped and owned production-grade pipelines at large scale (tens of TBs to PBs daily).
- A track record as a staff/principal-level individual contributor before moving into leadership — you earn the technical trust of a strong team.
- You've managed and grown a team (~5–10), or clearly demonstrated the leadership readiness to build one quickly — while staying technically embedded.
- Deep in at least one of: ingestion & orchestration at scale, storage and processing engines (lakehouse formats, query engines), or data quality/lineage/reproducibility systems — with working breadth across the others.
- Fluent in the modern data stack; you've built new systems from zero rather than maintained legacy ones.
- Thrive in a high-agency, fast-paced environment; bias toward action and impact.
- Collaborative, clear communicator, comfortable working across research and infrastructure boundaries.
Explore our comprehensive directory of visa sponsorship jobs from employers worldwide who are ready to sponsor talented international professionals.
We believe that to make intelligence open and accessible to all, you need to start at the foundation. Joining Reflection means building from the ground up as part of a talent-dense team. You will help define our future as a company, and help define the future of open foundational models.
We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported.
Interested in opportunities specifically in United State? Discover our dedicated Visa Sponsorship Jobs in United State page featuring roles from top employers in this location.
- Top-tier compensation: Salary and equity structured to recognize and retain our talent globally.
- Stock options: Everyone who joins and contributes to Reflection's success gets to share in the upside through stock options.
- Health & wellness: Comprehensive medical, dental, vision, and life, with an annual wellness allowance.
- Meals: Lunch and dinner are provided in the office daily.
- Life & family: 22 weeks paid parental leave for all new birthing and non-birthing parents, including adoptive and surrogate journeys.
- Vacation days: Unlimited paid time off in the U.S. and 30 days in the U.K.
- Sponsorship support: We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable.
- Team building: We have regular off-sites, happy hours, and team celebrations.
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