Hire Pre-Vetted Data Engineers in Under 14 Days
Every AI and analytics initiative lives or dies on its data pipelines. Get a senior data engineer who builds the reliable, scalable infrastructure your models and dashboards depend on — at $35/hour, in your time zone.
✔ Sub-14-day placement ✔ US time-zone overlap ✔ Vetted on real work ✔ Cancel anytime, 2 weeks’ notice
Why data engineers are the hidden bottleneck on every AI team
Everyone wants AI and analytics; far fewer realize those efforts stall without solid data engineering underneath. The pipelines, warehouses, and transformations that feed models and dashboards are unglamorous and absolutely essential — and the engineers who build them well are in short supply.
In the US a senior data engineer runs $175K–$230K with a long search. Divogue places data engineers vetted on real pipeline and warehouse work in under two weeks, so your data team stops being the thing that holds everyone else up.
What our data engineers are vetted on
Every data engineer we place is screened on building production data infrastructure, not one-off scripts.
| Area | What we test for |
|---|---|
| Pipelines | Airflow, dbt, ETL and ELT design, batch and streaming |
| Warehousing | Snowflake, BigQuery, Redshift, data modeling, partitioning |
| Processing | Spark, Kafka, SQL optimization, large-scale transformation |
| Cloud and ops | AWS, Azure, GCP, orchestration, data quality, monitoring |
| AI tooling | Daily use of Cursor, Claude, Copilot to ship faster |
What teams hire our data engineers for
Data pipeline development
Reliable ETL and ELT pipelines that move and transform data at scale without breaking.
Warehouse and lakehouse builds
Designing and building the Snowflake, BigQuery, or Redshift foundations your analytics run on.
Streaming and real-time data
Kafka and Spark pipelines for use cases that can’t wait for nightly batches.
AI and ML data foundations
The clean, well-modeled data infrastructure that every serious AI initiative depends on.
The same engineer, half the cost, a fraction of the wait
| In-House US Hire | Divogue Data Engineer | |
|---|---|---|
| All-in annual cost | $175K–$230K | ~$67K ($35/hr) |
| Time to start | 2–4 months | Under 14 days |
| Recruiting fee | 20–25% of base | $0 |
| Time-zone overlap | Full | Full US hours |
Calculate what you’d save
Drag the sliders to compare a Divogue data engineer against an in-house US hire.
Estimates based on a $35/hr Divogue rate at 160 hrs/month vs a $150K–$200K all-in US salary plus a ~22% recruiting fee. Actual figures vary by role and seniority.
Trusted by teams shipping in production
Divogue engineers are embedded with companies building real products today — including Riskcast, BGO Software, and everyone.ai — across construction technology, healthcare software, and ML infrastructure.
Frequently asked questions
What tools do your data engineers use?
Airflow and dbt for pipelines, Snowflake, BigQuery, and Redshift for warehousing, and Spark and Kafka for large-scale and streaming workloads.
How quickly can one start?
Most placements are live in under 14 days from your first call.
Can they support our AI and ML work?
Yes. Strong data engineering is the foundation of reliable AI, and our data engineers build the pipelines and infrastructure your models depend on.
Do they overlap US working hours?
Yes. We source from LATAM and APAC specifically for engineers who work your business hours.
What if the engineer isn’t the right fit?
Cancel with two weeks’ notice, no penalty. We’ll help you find a better match if you’d like to continue.
Book a free intro call
Pick a time that works for you. We’ll walk through your stack, your needs, and show you matched engineers within days.
Ready to add a data engineer to your team?
Book a free 30-minute call. Tell us about your data stack and we’ll show you matched engineers within days.