Staff Engineer, Ads Measurement & Orchestration

Cacheflow; New York (NY); On-site; USD 191,000 - 254,000; Full time

Job summary

Databricks is seeking an experienced engineer to lead ingestion and normalization of advertising platform data at scale. You will design aggregation and identity layers to compare figures across platforms, and drive agentic workflows that parse, interpret, present, and act on performance data.

You will ship LLM-powered systems with evaluation guardrails, collaborate closely with product, design, and engineering teams, and own impactful decisions in a fast-moving, 0→1 environment.

Qualifications

• 10+ years of engineering experience with leadership responsibilities.
• Hands-on experience with walled garden advertising APIs (Meta, Google, Amazon, TikTok).
• Working knowledge of ad tech data models: campaign hierarchies, attribution windows, conversion APIs.
• Experience shipping LLM-powered systems to production with eval and guardrails.
• Strong ownership and bias for action in 0→1 environments.

Responsibilities

• Lead the ingest and normalization path for advertising platform data at scale.
• Design the aggregation and identity layers that make figures from different platforms comparable.
• Lead development of agentic workflows that parse, interpret, present, and act on performance data.
• Set the correctness and evaluation bar in a domain with noisy ground truth.
• Partner with product, design, and other engineering teams to build scalable, extensible solutions.

Skills

Engineering leadership

Ad tech APIs

Data modeling

LLM systems

Cross-functional collaboration

Measurement frameworks

Job description

Databricks is seeking an experienced engineer to lead ingestion and normalization of advertising platform data at scale. You will design aggregation and identity layers to compare figures across platforms, and drive agentic workflows that parse, interpret, present, and act on performance data.

You will ship LLM-powered systems with evaluation guardrails, collaborate closely with product, design, and engineering teams, and own impactful decisions in a fast-moving, 0→1 environment.