Software Engineer
- Discuss this with your agent
- Open in Claude
- Open in ChatGPT
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Role details
Tech stack
+15 more
Job description
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.
Requirements
- 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., Analysis Skills, Application Programming Interface (API), Artificial Intelligence (AI), CPU (Central Processing Unit), Cloud Computing, Cost Modeling, Database Extract Transform and Load (ETL), Dental Insurance, Ecosystems, Entertainment and Media, GPU (Graphics Processing Unit), Go Programming Language (Golang), Instrumentation, Machine Tool, Product Engineering, Public/Media/Press/Analyst Relations, Python Programming/Scripting Language, Risk, SQL (Structured Query Language), Software Engineering, Startup, Systems Analysis, Telemetry, Usage Analysis, Vendor/Supplier Relations, Vision Plan, Warehousing
Apply for this position
This job is hosted externally. Click below to view the full posting and apply.
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Good distractions
Talks and stories from around this role — technically off-topic, practically not.
Moments
Explore playlistsVideos
See allRelated articles
See all
Dev Digest 120 - Apple and peers
How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again
Data Engineer Salary UK
Navigating the AI Shift