P-1607
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.
The impact you'll have:- 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
What we look for:- 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 01 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)
Pay Range TransparencyDatabricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
Local Pay Range
$190,900-$253,750 USD
