DataBricks Engineer

The Impact You'll Make

• Modernize: Refactor legacy codebases into high-performance PySpark pipelines.

• Build: Design end-to-end data workflows using Databricks Jobs, Workflows, and Delta Lake.

• Optimize: Fine-tune Spark job performance and cluster configurations for cost and speed.

• Lead: Implement CI/CD, data quality frameworks, and mentor junior engineers.

What You Bring

• Expertise: 8+ years in Data Engineering with 2-3 years of hands-on Databricks experience.

• Technical Core: Deep mastery of PySpark (DataFrames/SQL), Python, and Delta Lake.

• Architecture: Strong understanding of Dimensional Modeling, Data Vault, or Lakehouse patterns.

• Modern Ops: Experience with Git, CI/CD, and robust monitoring/alerting.

Mandatory Requirement

• Certification: Must hold either Databricks Certified Data Engineer Associate or Professional.