Job Description

As a Lead Databricks Engineer, you will play a critical role in delivering large-scale data transformation programs. You will lead the design and implementation of up-to-date Lakehouse platforms on Databricks, working closely with client stakeholders, architects, and cross-functional teams. This is a client-facing leadership role requiring strong consulting capabilities, technical depth, and delivery ownership.

The Lead Databricks Engineer is responsible for designing and implementing scalable data platforms using Databricks, Apache Spark, and Delta Lake, including building robust batch and real-time data pipelines and developing ingestion frameworks for both structured and unstructured data while optimising performance, cost, and reliability. The role involves leading and mentoring a team of data engineers, driving best practices across coding, CI/CD, and DevOps, and collaborating with cross-functional stakeholders to translate business needs into effective data solutions,



while owning end-to-end project delivery. Additionally, the engineer will implement data solutions across cloud platforms—primarily Azure, but also AWS or GCP—integrating with services such as Azure Data Factory, AWS Glue, and modern data warehouses like Snowflake or Synapse, while managing infrastructure through Infrastructure-as-Code tools. A strong focus is placed on data governance, including implementing quality checks, monitoring and observability frameworks, ensuring compliance with security and privacy standards, and managing metadata and lineage using tools like Unity Catalog. The role also supports advanced analytics by enabling data science workflows, building ML-ready datasets using Databricks capabilities, and supporting real-time analytics through technologies such as Structured Streaming and Delta Live Tables.

📌 Databricks Solution Lead (Adelaide)
🏢 NCS Australia
📍 Adelaide