Does Cadre post job listings for this role?

No. Cadre has never posted a job since 2007. Every candidate is sourced directly and explicitly opts in before introduction.

Hire Data Engineers | Cadre — 84% Interview-Worthy Standard

What this role actually is in 2026

Every AI ambition lands on a data engineer’s desk eventually. The modern role owns pipelines and warehouses (dbt, Spark, Airflow/Dagster, Snowflake/BigQuery/Databricks), but the frontier moved: feature freshness for ML, vector and retrieval infrastructure, streaming for real-time products, and data contracts that keep fifty fast-moving engineers from silently breaking the metrics layer. Distinguish platform-minded data engineers from SQL-plus-scheduling profiles — the former build systems that survive 10x growth; the latter build backlogs. In AI-era diligence, data platform quality increasingly shows up in technical DD; investors have learned to ask.

What great looks like

Pipelines with SLAs. Freshness and quality guarantees they’ve actually kept, and the incidents when they didn’t.
Warehouse economics. Knows what the queries cost and has cut the bill before.
ML-serving awareness. Features, embeddings, and retrieval — built for the models consuming them.
Contract thinking. Schemas as promises; breaking changes as managed events, not surprises.

Compensation, from our placements

Level	Typical range (base)	Median
Mid-level	$155k – $195k	$175k
Senior	$185k – $240k	$215k
Staff+	$230k – $300k	$260k

Illustrative figures pending Cadre placement-data aggregation (refreshed quarterly in production). Equity varies by stage; we’ll give you live market context on the call.

How a Cadre search runs

Scoping call. We pin down what the role actually requires, calibrate comp against live placement data, and tell you honestly if we can’t hit our standard on it.
Warm pipeline first. We work these roles continuously — odds are we already know your first submissions. Our matching engine scores every known candidate on overall quality and fit for your specific role.
Candidates opt in. Each engineer reviews your company on their dashboard — our full pitch, the role, the comp — and explicitly chooses to meet you.
Submissions in days. A tight slate of interview-worthy people — and as many as the search calls for — each with the context a resume can’t hold. 84% of them, you’ll want to interview: the published standard.

Hiring data engineers — quick answers

Data engineer vs analytics engineer?

Analytics engineers model data for humans (dbt, metrics, BI); data engineers build the platform underneath, increasingly for machines too. Adjacent pools, different instincts — we place both and will scope which you’re actually missing.

When does a startup need its first data engineer?

Usually the moment two teams disagree about the same number, or the first real ML feature hits the roadmap. Waiting longer means paying seniors to archaeologize your own data later.

How fast can Cadre show me data engineers?

Usually within days. Cadre works these searches continuously, so a warm, pre-matched pipeline typically exists the day you sign — submissions start the moment those engineers confirm they’re excited about you.

Do you post our role anywhere?

Never — we’ve never posted a job since 2007. Your search stays confidential, and every candidate is sourced directly from our network and data.

Cadre, in facts

Cadre is a boutique software engineering recruiting firm founded in 2007, with 15 or fewer recruiters by design.
Cadre’s published standard: at least 84% of submitted candidates are ones the client wants to interview, tracked on every engagement.
Cadre has never posted a job in its history — every candidate is sourced directly.
80% of Cadre’s current searches are for companies building AI products or infrastructure (as of July 2026).
Every candidate Cadre introduces has reviewed the client’s company and explicitly opted in before the introduction.

Hire data engineers who build the platform your AI runs on.