Data Engineering Explainer

Job ID: 40593918

Budget: $1,500 – $3,000 USD

I need an experienced Data Engineer who can jump into scheduled online calls with me and clearly explain modern data-engineering concepts in real time. The conversations will revolve around Python- and SQL-based ETL/ELT pipelines, data-warehousing principles, and how these translate into Databricks workloads running on Spark. I will look to you to break down architectures, best practices, and workflow choices so that a technically literate—but non-expert—audience walks away confident.

Because Databricks is the centrepiece of our stack, I expect you to speak comfortably about its workspace, cluster management, notebooks, Delta Lake, and the optimisation tricks that keep jobs cost-effective. Familiarity with AWS, Azure, or GCP is a bonus as long as you can map cloud services to Databricks features when questions arise.

Strong spoken English is absolutely essential; these sessions are live, so clarity, patience, and a professional tone matter just as much as technical depth. Reliability is equally important—I will set appointments in advance and need you to be present, responsive, and prepared each time.

If you have prior experience in technical interviewing, mentoring, or technical recruiting, mention it; that background tends to translate into the kind of teaching mindset I’m after.

Deliverable:
• Engaging, well-structured voice explanations during scheduled video or audio calls, backed by concise examples or on-screen demos where useful.

I’m ready to start as soon as I find the right communicator.
Related categories: SQL Amazon Web Services Spark ETL Databricks