Data engineers who build the plumbing every downstream team depends on.
We place senior data engineers at companies where the data stack is genuinely load-bearing — analytics, ML features, product reporting, and finance close. Vetted for modeling discipline, pipeline reliability, and SQL depth.
The senior data engineer market — the honest version.
Data engineering sits at the intersection of backend discipline, SQL depth, and analytics judgment. The best senior data engineers design systems other teams can self-serve from; the weaker ones build brittle pipelines and disappear. Our screen separates them by asking for a real system the candidate designed, tracing the trade-offs, and testing SQL fluency directly — not via a take-home.
What we actually screen for.
Every senior data engineer candidate goes through a structured technical screen conducted by an ex-engineer recruiter before you see their profile.
- Warehouse depth — Snowflake / BigQuery / Redshift / Databricks, partition strategy, cost discipline
- Orchestration fluency — Airflow / Dagster / Prefect, DAG design, retry and alerting discipline
- Modeling rigor — dbt, dimensional modeling, data-vault, slowly-changing dimensions, testing
- Streaming experience — Kafka / Flink / Kinesis if relevant to your stack
- SQL fluency — window functions, CTEs, optimization — tested live, not via take-home
- Data quality posture — Great Expectations, dbt tests, or equivalent, not as an afterthought
How we run a senior data engineer search.
Days 0–2
Intake + stack alignment
Clarify warehouse, orchestration, modeling layer, and downstream consumers (analytics, ML, product, finance).
Days 2–12
Sourcing + SQL screen
Live SQL scenario + modeling discussion + orchestration deep-dive.
Days 10–14
First shortlist
4–6 candidates with written assessments including examples of shipped pipelines.
Days 14–24
Interviews + offer
Coordinated loop including data architecture and cross-team partner conversations.
Real salary bands across our three markets.
- Pakistan (remote int'l)
USD $40K–$110K
- Canada
CAD $125K–$200K + equity
- United States
USD $160K–$270K + equity
Titles we place under this role type.
- Senior Data Engineer
- Analytics Engineer
- Staff Data Engineer
- Senior Platform Data Engineer
- Senior ETL Engineer
- Data Architect
Senior Data Engineer hiring — questions we hear.
Data engineers build the ingestion, storage, and orchestration layers. Analytics engineers (a newer specialization) own the modeling layer — dbt, semantic layer, metrics definitions. Some companies conflate them; we calibrate the shortlist against which you actually need.
Ready to run this search?
Submit a brief and a senior recruiter will reply within 24 business hours with a proposed timeline, calibrated fee structure, and sample profiles.
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