Senior Databricks Engineer

Job Summary

The Senior Databricks Engineer at LAKEORA is responsible for managing the entire lifecycle of Databricks implementations, including discovery, architecture, delivery, and client demonstrations. The role involves direct client interaction, shaping data platform strategies, and ensuring solutions reach production.

Responsibilities

• Develop scalable data pipelines using Spark (PySpark and SQL) on Databricks.
• Lead or assist in technical discovery sessions with potential clients, documenting insights and defining solution strategies.
• Conduct customized technical demonstrations of the Databricks platform highlighting business and technical value.
• Convert client requirements into delivery scopes and effort estimates collaboratively with the team.
• Serve as technical lead throughout client projects from architecture design to implementation.
• Implement sound engineering practices such as code reviews, unit testing, Git usage, and Agile methodologies.
• Mentor junior engineers and help elevate the technical standards of the team.
• Keep updated on new trends and best practices in Databricks, Data, GenAI, and AI.

Must haves

• At least 5 years of data engineering experience with hands-on Spark development (PySpark and SQL).
• Strong conceptual understanding of SQL fundamentals.
• In-depth knowledge of Databricks concepts including Lakehouse, Medallion, Delta Lake, and Unity Catalog.
• Practical experience with Databricks features such as Lakeflow Jobs, Declarative Pipelines, AI/BI Dashboards, and Genie.
• Cloud experience with one or more hyperscalers: Azure, AWS, or GCP.
• Solid grasp of data warehousing, data modeling, ETL/ELT design, and pipeline architecture.
• Effective communication skills to engage both technical and business stakeholders.
• Experience with version control (Git) and CI/CD tools.
• Degree in Computer Science, Software Engineering, Mathematics, or related STEM field.

Nice to haves

• Databricks certifications (Data Engineer Associate or Professional preferred).
• Experience in consulting or client-facing delivery roles.
• Familiarity with streaming technologies like Kafka or Spark Streaming.
• Exposure to manufacturing, supply chain, or logistics data domains.
• Knowledge of Data & AI regulations in Saudi Arabia.
• Experience with AI and GenAI technologies such as Claude Code, RAG, Agents.

We refresh listings regularly, but some roles close early on the source platform.