Of the ten postings, Datadog's is the most revealing because it casually name-drops infrastructure choices that most companies would treat as multi-year platform bets. The tell: "We build our own tsdb, distributed tracing tools, cutting edge visualizations... process trillions of events per day."

The stack decoded:

• Go, Python, Java, React — a polyglot backend is a green flag for engineers who hate monocultures, but a signal that different teams own different services with different constraints (Go for hot paths, Java for JVM ecosystem integrations, Python for data/ML).
• Custom TSDB — they didn't adopt InfluxDB or Prometheus at scale; they built their own time-series database. This is a company that has passed the point where off-the-shelf storage engines can handle their cardinality.
• k8s, multi-region, multi-cloud — not just "we use Kubernetes" but explicit multi-cloud, which is expensive, complicated, and only justified when your customers demand cloud parity (or you're hedging against a single provider).

What the posting reveals about stage and direction: Datadog is well past product-market fit and squarely in "scale eats everything" mode. The phrase "trillions of events per day" is the entire pitch — they're not selling a mission, they're selling the problem itself. Engineers who like monitoring will self-select in; everyone else bounces. That's a confident, mature recruiting move.

The three-office ONSITE list (Boston, NYC, Paris) plus REMOTE tells you they've committed to distributed work but still cluster engineering leadership on both coasts and in Europe — a hedge that gives them talent access without going fully async.

Skills/trends highlighted: The observability space is consolidating around vendors who own their storage layer. If you're a systems engineer with distributed-storage or query-engine experience, this posting is a beacon. It also confirms the industry-wide shift where "monitoring" companies are really "distributed database" companies wearing a UI.

Green flags: Concrete tech, concrete scale numbers, named regions, and the phrase "customers just like us" (dogfooding). Red flags: Extremely terse — no mention of comp, level, team structure, or what "Software Engineers" actually means at a company with hundreds of them. That vagueness is a filter; it works for Datadog because their brand does the recruiting, but it would sink a smaller company.