Senior Data Engineer, GTM at Google
Mountain View, CA
$156,000–$227,000from the description
Jul 9, 2026
Mountain View, CA
Jul 21, 2026
What this job asks for AI summary
This role centers on building and owning the data infrastructure that converts large volumes of unstructured customer and sales conversation data into structured insights for Ads product teams. Day-to-day work involves designing ingestion and processing pipelines, developing LLM and AI-agent tooling, managing embedding workflows with TensorFlow and TPUs, and creating self-serve frameworks for NLP and causal analysis. It suits an experienced data engineer with a strong background in MLOps/LLMOps and Python/SQL.
Senior level · 5+ years · Mountain View, CA · Full-time
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 4 people in the Mountain View, CA area plausibly meet what this posting asks for (database architects). range 2–6
Applicant volume Light — Few people clear these requirements, so an application that does clear them gets looked at. Worth applying to even if you miss a nice-to-have.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $202,313 (middle half $144,101–$222,457). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (7)
The role is posted with multiple possible work locations: Mountain View, CA; Chicago, IL; Irvine, CA; and New York, NY. Mountain View (Google HQ) is listed first and used as the primary CBSA.
The JD internally labels this role 'Mid' in its experience-level framing ('Mid Experience driving progress…'), but the title is 'Senior Data Engineer' and the 5-year requirements and scope (architecting foundational infrastructure, end-to-end production delivery) support a Senior classification.
Compensation is stated as $156,000–$227,000/year plus a 15% bonus target and equity; the bonus and equity are not captured in the comp fields, which reflect base salary only.
The degree requirement is 'Bachelor's degree or equivalent practical experience,' which means equivalent experience is accepted — treated as no hard degree gate.
Data schemas appear in both the required and preferred sections; the required mention is tied to the pipeline design requirement (5 years), while the preferred section lists it again as a standalone item — this duplication appears to be a drafting artifact.
The SOC classification is a close call between 15-1243 (Database/Data Architects, for pipeline and infrastructure building) and 15-2051 (Data Scientists, given the heavy ML/LLM/NLP focus). The primary day-to-day work described — architecting and deploying data pipelines and infrastructure — tips toward 15-1243.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): LLM orchestration.
Read the full posting
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