Senior Databricks Engineer

About LAKEORA

Role overview

Key responsibilities

• Design and build scalable Databricks data pipelines using Spark, PySpark, and SQL.
• Lead or support client discovery, document findings, and shape solution approaches.
• Deliver tailored technical demonstrations that explain business value and technical details.
• Turn client requirements into delivery scopes and effort estimates with the broader team.
• Lead client engagement technical work from architecture through implementation.
• Use code reviews, unit testing, Git, and Agile delivery practices.
• Mentor junior engineers and contribute to the team’s technical standards.
• Keep current with Databricks, data, GenAI, and AI trends and practices.

Required qualifications

• 5+ years of data engineering experience with hands-on Spark development using PySpark and SQL.
• Strong conceptual SQL fundamentals and deep understanding of Databricks Lakehouse, Medallion, Delta Lake, and Unity Catalog.
• Hands-on Databricks experience with Lakeflow Jobs, Declarative Pipelines, AI/BI Dashboards, and Genie.
• Experience with one or more of Azure, AWS, or GCP.
• Solid knowledge of data warehousing, data modeling, ETL/ELT design, and pipeline architecture.
• Strong communication skills for engaging technical and business stakeholders.
• Experience with Git or other version control and CI/CD tools.
• Degree in Computer Science, Software Engineering, Mathematics, or a related STEM field.

Preferred qualifications

• Databricks Data Engineer Associate or Professional certification is strongly preferred.
• Consulting or client-facing delivery experience is preferred.
• Kafka or Spark Streaming experience is preferred.
• Exposure to manufacturing, supply chain, or logistics data domains is preferred.
• Exposure to Saudi Arabia Data & AI regulations is preferred.
• Exposure to AI and GenAI, including Claude Code, RAG, or agents, is preferred.