Data engineering — a Lakehouse ecosystem
Data engineering specialists, matched to your stack
Describe what you're building — the stack, the scale, the outcome. We'll match it to data engineers, lakehouse & warehouse architects, and ML specialists who've shipped it before, across Databricks, Snowflake, Microsoft, Spark, and dbt. Profiles are anonymized.
Databricks, Snowflake, Microsoft Fabric, Apache Spark and dbt are trademarks of their respective owners, used here only to describe specialists’ experience. Lakehouse is an independent talent network operated by Sloane Staffing; none of these vendors endorses or sponsors this site.
What the Data Engineering network covers
These are the capabilities specialists in the Data Engineering network are qualified on — and the same vocabulary your brief is read against, so anything named here is something you can search for above.
- Databricks Platform
- Snowflake
- Microsoft Data Platform
- Apache Spark
- PySpark
- Delta Lake
- Unity Catalog
- Lakehouse Architecture
- Data Engineering
- ETL / ELT Pipelines
- Streaming Data
- Data Modeling & Warehousing
- SQL
- MLflow
- Machine Learning & MLOps
- GenAI & LLMs
- Orchestration (Airflow / Workflows)
- dbt
- Cloud Platforms (AWS / Azure / GCP)
- Data Governance
- Python
- Scala
- Terraform & CI/CD
FAQ
How does Lakehouse match data engineers to my brief?
Paste a job description or a rough description of what you are building. We read it into a structured requirement — the primary capability, the ones that matter, and the nice-to-haves — then search the data engineering network against it and show you who covers it and how closely. If we understood the brief but do not have the person, the page says so rather than showing you adjacent profiles as though they fit.
Which data engineering skills are in the network?
The network is organised around the lakehouse and the modern data stack: Databricks, Snowflake, and the Microsoft data platform (Fabric, Synapse, Azure Data Factory); Apache Spark, PySpark, Delta Lake and Unity Catalog; lakehouse architecture, ETL/ELT pipelines, streaming, data modeling and warehousing, and SQL; dbt and orchestration with Airflow; MLflow, machine learning and MLOps, and GenAI/LLM work; plus data governance, AWS/Azure/GCP, Python, Scala, and Terraform and CI/CD. Those are the same categories a brief is matched against, not a keyword list.
Do you cover contract as well as permanent hires?
Both, through the same network. Some briefs need a specialist for one implementation and some need the person who builds the practice behind it, and the shortlist is drawn from the same bench either way — tell us which shape you need in the brief.
What does it cost to search?
Nothing. Searching is free and needs no account — no sign-up wall, no credit card, and you are not added to a sequence for running a search. A fee applies only if you go on to hire someone Sloane introduces, and it is agreed with you before any introduction is made.
Why are the profiles anonymized?
So you judge the work first. An anonymized profile shows what the specialist has actually built and shipped, without a name or a CV format pulling attention away from it. Before any introduction, Sloane confirms the specialist's availability, interest and fit for your brief — so the conversation you get is worth having.
More on how the practice works: Why Sloane.