Leading the architecture and delivery of large-scale Databricks Lakehouse solutions
Driving Databricks migration and modernisation projects
Advising clients on Databricks best practices, capability uplift and roadmap development
Guiding cross-functional delivery teams and supporting capability growth across engineering and analytics
Establishing scalable patterns, reusable assets and improvements to Databricks delivery approaches
Coaching consultants and team leads on Databricks engineering, governance, optimisation and platform design
Contributing to Snap’s internal Databricks initiatives, thought leadership and go-to-market strategy

Deep, hands-on experience with Databricks, including:
Lakeflow Jobs and Lakeflow Declarative Pipelines
Autoloader and similar spark structured streaming patterns
PySpark and Spark SQL
Implementing CI/CD pipelines using Databricks Asset Bundles
Unity Catalog and data governance including attribute based access controls
Strong knowledge of python and SQL
Experience deploying and managing Databricks workspaces with IaC tools like Terraform
Strong experience in at least one cloud platform (Azure, GCP, AWS)
Experience with enterprise extraction tools like Fivetran, HVR and Azure Data Factory, and their integration with a Databricks platform
Experience leading large, complex data platform deliveries
Strong architectural thinking across ingestion, transformation, modelling, orchestration and governance
Clear communication skills and confidence working with a range of stakeholders
A practical, outcomes focused approach that connects technical delivery to business value

Senior Data Platform Consultant – Databricks

Key skills