Staff Software Engineer, Ads Measurement & Orchestration
Databricks · New York City, New York · Engineering - Pipeline · listed August 28, 2026
The shape of it
Seniority
Staff
Experience asked
10+ years
Where
Not stated
Stated pay
$190,900 – $253,750 USD
Requirements listed
10
Length
804 words
In the posting’s own words
Enterprises spend more than $700 billion on digital advertising, however for the most part, they have very little data & intelligence on how their campaigns are performing. Reconciling that is slow, manual, and mostly wrong, and optimizing those campaigns historically has involved humans and agencies. We are building the data and agent layer underneath that problem, and we are looking for an engineer to help lead that effort.
What it asks for · 10
- 10+ years of engineering experience, including time as a tech lead or leading other tech leads, on complex enterprise software projects
- Hands-on experience with walled garden advertising APIs (Meta, Google, Amazon, TikTok) or the equivalent from the advertiser, agency, or DSP side
- Working knowledge of ad tech data models: campaign hierarchies, attribution windows, conversion APIs, deduplication across sources
- Familiarity with measurement approaches such as MTA, MMM, incrementality testing, and privacy-preserving aggregation
- Experience shipping LLM-powered systems to production, including evaluation and guardrails
- High ownership and bias for action in 0→1 environments: you are comfortable making pragmatic trade-offs, operating with incomplete information, and driving projects from idea through launch and adoption
- Strong ability to collaborate across product, engineering, and design teams to align technical strategy with company growth objectives
- Combination of technical and people leadership, for example, as a TLM (Nice to have)
- Built or operated measurement infrastructure at a platform, measurement vendor, or large advertiser (Nice to have)
- Background in experimentation or causal inference (Nice to have)
What the job covers
- Lead the ingest and normalization path for advertising platform data at scale, including rate limits, schema drift, backfills, and restated numbers
- Design the aggregation and identity layers that make figures from different platforms comparable
- Lead development of agentic workflows that parse performance data, interpret it, present it, and act on it
- Set the correctness and evaluation bar in a domain where ground truth is noisy and partially observable
- Partner closely with product management, design, and other engineering teams to build intuitive, scalable, and extensible solutions that drive user & business growth
Tools and skills named
Data
- Databricks
- Experimentation
Models & research
- Inference
- LLM
Product & design
- Product management
- User experience
Ways of working
- Testing
Words the posting leans on
- data9×
- lead5×
- platform4×
- advertising3×
- campaigns3×
- design3×
- engineering3×
- experience3×
- measurement3×
- nice3×
- tech3×
- technical3×
- advertiser2×
- aggregation2×
- apis2×
- building2×
Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.
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