fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products.

As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on.

About this role:

As a Senior Data Engineer at fal, you will build the data infrastructure that turns our internal systems and external vendor relationships into a clear picture of cost, margin, and performance. Your work spans both edges of our stack - the production infrastructure that runs every model invocation, and the partner APIs and compute vendors whose costs we need to reason about in near real-time.

This role sits at the intersection of software engineering and data engineering. You'll partner closely with Infra to safely instrument core systems, design a low-latency analytical write path, and stand up the ingestion pipelines that unlock cost, margin, and infrastructure analytics for the entire company. You will be a force multiplier - freeing up product engineers and infra to focus on what they do best while giving the data team the foundations it needs to move fast.

What you'll do

Instrument fal's core infrastructure to capture CPU, GPU, and request-level signals, working alongside our infra team to land changes safely in critical paths.
Build ingestion pipelines from partner APIs, compute vendors, and internal services into BigQuery and a new low-latency analytical store (e.g., ClickHouse).
Design and operate the ETL backbone that powers cost, margin, and usage analytics with durable, observable pipelines.
Stand up a lightweight, low-latency write path that the data team and product engineers can target directly for analytics-grade telemetry.
Partner with infra, data and product engineering to define data contracts and instrumentation standards, and act as the connective tissue between operational systems and the analytics layer.

What we are looking for

5+ years of experience as a software or data engineer, with a software-engineering-heavy track record (Python, Go, or similar)
Demonstrated ability to ship code into critical production infrastructure safely, including familiarity with database performance, query patterns, and incident risk.
Hands-on experience building ingestion pipelines into a warehouse (BigQuery, Snowflake, Redshift) and at least one low-latency analytical store (ClickHouse, Druid, Pinot, or similar).
Strong SQL and working proficiency in dbt and orchestration tooling (Dagster, Airflow, Prefect).
Track record of partnering across teams (infra, product engineering, data) and translating business questions into durable systems.
Bias for action and comfort working in fast-moving, ambiguous environments.

Nice-to-haves

Experience instrumenting GPU/accelerator workloads or other infrastructure-cost-heavy systems.
Exposure to FinOps or infrastructure cost modeling at a cloud-native company.
Experience with developer-facing API products or platforms.
Early-stage or fast-scaling startup experience.