Databricks Data Engineer

About The Role
You’ll build and run lakehouse platforms on Databricks for our North American and European clients — ingestion pipelines, Delta Lake architectures, transformation layers and the governance around them. This is client-facing engineering: you’ll present your work in the client’s standup, own outcomes end to end, and work with modern data stacks in production, not in a sandbox.
What you’ll do
Design and build batch and streaming pipelines with Spark, Delta Live Tables and Delta Lake
Implement medallion architectures with Unity Catalog governance
Migrate legacy warehouses (Redshift, Snowflake, on-prem) to the lakehouse
Optimize cluster configuration and pipeline cost — and explain the trade-offs to clients
Work directly with client engineering teams in US and European timezones (structured overlap hours, not night shifts)
What we’re looking for
3–6 years in data engineering, with at least one year of hands-on Databricks or serious Spark experience
Strong Python and SQL — you write code that other engineers review and reuse
Experience running pipelines in production: monitoring, incident handling, backfills
Clear written and spoken English — you’ll communicate directly with clients
Databricks certification is a plus; if you don’t have it, we’ll pay for you to get it
What you get
Databricks, AWS and Retool certification costs and prep time covered
Direct client exposure and ownership from your first month
Structured timezone overlap — evenings are for occasional calls, not a permanent shift
A small, senior team where your work is visible
To apply, email your CV to info@zephico.com with the subject “Application: Databricks Data Engineer”.

Work arrangement
No