Databricks Solution Architect

About the role

We are looking for a hands‑on Databricks Solution Architect to design, develop and operationalise Lakehouse‑based data and AI solutions for enterprise customers. You will own implementation tasks, lead technical delivery and mentor engineering teams on best practices across data engineering, governance and AI.

Key responsibilities

• Design and implement scalable data pipelines using Delta Live Tables, Spark SQL, Python or Scala.
• Optimise ETL, streaming and machine‑learning workloads for performance, cost efficiency and reliability.
• Administer and configure Databricks Workspaces, Unity Catalog and cluster policies to ensure secure, governed environments.
• Automate infrastructure and deployments with Terraform, Git and CI/CD pipelines.
• Implement observability, cost‑optimisation and monitoring frameworks using tools such as Splunk, Prometheus or CloudWatch.
• Collaborate with customers to build AI and LLM solutions leveraging MLflow, DBRX and Mosaic AI.

Required profile

• 10+ years of hands‑on experience with Databricks, including workspace setup, notebooks, clusters and job orchestration.
• 8+ years of experience with Apache Spark and strong proficiency in Python or Scala.
• Solid understanding of AWS, Azure or GCP cloud ecosystems.
• Proven experience with Terraform automation, DevOps and MLOps practices.
• Familiarity with monitoring and governance frameworks for large‑scale data platforms.

Required skills

• Databricks
• Delta Lake
• Delta Live Tables
• Unity Catalog
• SQL Warehouses
• Apache Spark
• Python
• Scala
• AWS
• Azure
• GCP
• Terraform
• Git
• CI/CD
• Splunk
• Prometheus
• CloudWatch
• MLflow
• DBRX
• Mosaic AI