Matched to your stack in about a week. Vetted for the work, never swapped for someone cheaper. How we vet →

Talent·By Discipline·Data

Hire Data Engineers.

Pipelines, warehouses, and the unsexy work everything else depends on.

Senior data engineers embedded in your team through staff augmentation. The discipline most companies underinvest in until it bites them. Lateral data engineers know how to build pipelines that don’t silently drop rows, warehouses that don’t cost a fortune, and dashboards leadership actually trusts.

What they do

They ship ETL/ELT pipelines, dbt models, Airflow / Dagster orchestration, warehouse architecture, and the BI layer above it.

They ship ETL/ELT pipelines, dbt models, Airflow / Dagster orchestration, warehouse architecture, and the BI layer above it. They speak SQL fluently and can argue the merits of Iceberg vs. Delta over a coffee.

Common stacks

What they bring to the table.

SQLPythondbtAirflowDagsterSnowflakeBigQueryDatabricksIcebergDelta LakeKafkaFivetranLookerHexMode

Sample profiles

Real engineers. Anonymised.

Profiles below are from current network members, anonymised to protect their next move.

Ana T.

Senior Data Engineer · 8 yrs

"Cut warehouse spend 41% by replatforming the dbt graph."

PythondbtSnowflakeAirflow

Lisbon · UTC+0

Bruno K.

Staff Analytics Engineer · 10 yrs

"Built the metrics layer powering an exec dashboard a CFO trusts."

SQLdbtBigQueryLooker

Berlin · UTC+1

Camila S.

Senior Data Platform Engineer · 7 yrs

"Migrated 12 TB of analytics off Hive without downtime."

IcebergSparkKafkaDatabricks

Mexico City · UTC−6

Why hire through Lateral

Three reasons engineering leaders choose us.

  • 01Top 1%, vetted by engineers, not recruiters. Every Data candidate is reviewed by a senior in the same discipline. No keyword matching, no leetcode.
  • 02Matched in 7 days, in your time zone. We don't place engineers more than ~4 hours off your business day.
  • 03Transparent pricing. 60/25/15: most of what you pay reaches the engineer. See the breakdown.

FAQ

Honest answers, common questions.

Can they own a warehouse rewrite end-to-end?
Yes. Including the migration plan, the rollback strategy, and the conversation with finance about cost.
Do they care about data contracts?
They’ll bring it up before you do. Schema drift is the most common failure they prevent.
Will they help with ML feature stores?
Increasingly the same skill set. Most of our data engineers can hand off cleanly to an ML engineer or run feature engineering themselves.

Hire Data talent.

Tell us the role. Shortlist by next week.

Work with LateralEngineers · Teams · Entire builds
Let’s talk