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Databricks
New York City, New York, New York
At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. 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
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…
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