Databricks Engineer – Lakehouse Platform

About the role

The Databricks Engineer designs, builds and operates modern analytics and data platforms on the Databricks Lakehouse Platform. You will enable organisations to deliver scalable, high‑performance, governed data solutions across analytics, business intelligence, data engineering, data science and AI/ML workloads.

Key responsibilities

• Design and implement modern data platforms using the Databricks Lakehouse Platform.
• Build ingestion and transformation pipelines with Databricks Workflows, Apache Spark (PySpark / Spark SQL) and Delta Lake for batch, streaming and near‑real‑time processing.
• Define platform standards for data ingestion, modelling, quality and governance, ensuring alignment with cloud, security, identity and cost‑management requirements.
• Develop and optimise Databricks pipelines and Delta Lake models to support governed data consumption (e.g., Power BI, Tableau) and analytics, data‑science and ML use cases.
• Implement monitoring, performance tuning and cluster optimisation; support CI/CD for notebooks, jobs and pipelines; contribute to operational runbooks.
• Collaborate with analysts, data scientists and application teams, advise stakeholders on Databricks capabilities, and mentor junior team members where applicable.

Required profile

• 6–9 years of experience in data and analytics, with 4–6 years delivering modern data platforms using Databricks.
• Strong delivery, design and stakeholder‑engagement skills.
• Databricks Certified Data Engineer (Associate or Professional) and/or Databricks Certified Data Architect.
• Cloud platform certifications (Microsoft Azure or Amazon Web Services) are desirable.

Required skills

• Databricks Lakehouse Platform
• Apache Spark
• PySpark
• Spark SQL
• Delta Lake
• Structured Streaming
• Kafka