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Why Sloane

A data engineering practice, not a job board.

Sloane Staffing was founded in 2017 by a former Adobe account executive who kept watching companies buy powerful software and then struggle to hire the people who could actually run it. 9 years on, that is still the whole job — and the Lakehouse bench is the data engineering side of it.

Data engineering only

We recruit inside the lakehouse ecosystem — Databricks, Snowflake, Microsoft Fabric and the dbt, orchestration and streaming tooling around them. No generalist placements.

Evaluated on delivery, not keywords

Every specialist is qualified on the problems they have actually solved, not on years of experience or a list of technologies they have sat near.

Contract and permanent

One partner for both — a project-based contractor for an implementation, or the person who builds the practice behind it.

We know where the work is going

We track where consulting firms and platform teams are investing, and which capabilities are about to be in demand — usually before the requirement is urgent.

Specialists talk to us early

Experienced engineers build a relationship with us long before they are on the market, which is why the bench you are searching is not the same as a job board.

Anonymous until you decide

Profiles carry no names or employers. We confirm interest, availability and fit before any introduction, so nobody is put in front of you who does not want the work.

Partnerships

We work with the consulting firms and systems integrators building lakehouse delivery teams, and alongside Databricks and Snowflake account and customer-success teams staffing new implementations. Adobe Experience Cloud is the practice this firm was originally built around.

Companies we've hired for

Across go-to-market, technical and data roles since 2017.

6senseCockroach LabsClayCommon RoomcommercetoolsBrightflagIsland1MindBaseProfound

Ready when you are

Pick the specialists worth a closer look and we'll review them against your initiative — availability, interest, compensation expectations, and how closely their implementation experience actually matches what you're building.

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