Middle Databricks Data Engineer ID86295

AgileEngine, Remote (Ukraine only)

Що робити

● Design, build, and operate batch and streaming data pipelines on Databricks using PySpark, Delta Lake, and Databricks Workflows.
● Model and maintain a medallion (bronze/silver/gold) architecture serving analytics, reporting, and machine learning consumers.
● Migrate legacy ETL and data warehouse workloads onto the Lakehouse with validated data parity and minimal business disruption.
● Use Claude or Github Copilot as a development accelerator, generating code scaffolding, writing and reviewing tests, creating documentation and prototyping solutions.
● Write clean, well-tested Python and SQL; maintain high standards through code review and documentation.

● 3+ years of professional experience in data engineering, featuring direct expertise with Apache Spark and cloud-based data architectures.
● Strong hands-on experience building data pipelines with Databricks, Apache Spark (PySpark), and Delta Lake.
● Advanced SQL and Python, with strong data modeling skills across dimensional and Lakehouse patterns.
● Experience with streaming ingestion using Structured Streaming, Auto Loader, Kafka, or Event Hubs.
● Experience with workflow orchestration (Databricks Workflows, Airflow, or Azure Data Factory).

If you’re looking for a place to grow, make an impact, and work with people who care, we’d love to meet you! :)
About the role
We are looking for a Middle Data Engineer to help modernize a 15-year-old data warehouse into a governed Databricks Lakehouse. You will build batch and streaming pipelines with PySpark and Delta Lake, following a medallion architecture across bronze, silver, and gold layers. This role also uses AI tools like Claude and GitHub Copilot to speed up development.