Middle Databricks Data Engineer ID86295

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).

Experience with Infrastructure as Code (IaC) using Terraform and CI/CD using Azure DevOps.
Experience working with relational databases (specifically PostgreSQL) and data persistence concepts.
Familiarity with logging and monitoring tools (e.g., Dynatrace, CloudWatch, Databricks system tables).
Experience working in Agile or team-based development environments preferred.
The benefits of joining us

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