Senior Databricks Solution Architect

Unison Group; Norwich; On-site; GBP 120,000 - 160,000; Full time

Job summary

Unison Group is seeking a Senior Databricks Architect to design, implement, and optimize enterprise-scale data platforms using the Databricks Lakehouse Platform. The role requires deep expertise in Databricks architecture, Apache Spark, Delta Lake, and data engineering across cloud environments.

Key responsibilities include leading end-to-end Databricks implementations, defining security and governance models, and guiding data engineers, data scientists, and analysts.

Qualifications

• Experience designing enterprise Databricks solutions.
• Strong knowledge of Spark, Delta Lake, and Lakehouse architecture.
• Experience with cloud Databricks on Azure, AWS or GCP.

Responsibilities

• Design and architect Databricks Lakehouse solutions for large-scale data platforms.
• Lead end-to-end Databricks implementation including architecture, development, deployment and optimization.
• Define workspace architecture, cluster strategies, security models and operational standards.
• Design and develop scalable data pipelines using Databricks, Spark, PySpark, SQL and Delta Lake.
• Implement data ingestion frameworks for batch and real-time data processing.
• Lead migration projects from legacy data platforms to Databricks Lakehouse.

Skills

Databricks Platform

Apache Spark

Delta Lake

PySpark

SQL

Data Lakehouse

ETL/ELT

Cloud Platforms

Azure Databricks

AWS Databricks

GCP Databricks

Databricks Workflows

Notebooks

Repos

Cluster management

Unity Catalog

Security models

Tools

Databricks Workflows

Jobs orchestration

Notebooks

Repos

Cluster management

Unity Catalog

Job description

We are seeking a Senior Databricks Architect to design, implement, and optimize enterprise-scale data platforms using theDatabricks Lakehouse Platform. The ideal candidate will have deep expertise in Databricks architecture, Apache Spark, Delta Lake, data engineering, cloud platforms, and enterprise data solutions.

Key Responsibilities

• Design and architectDatabricks Lakehouse solutionsfor large-scaleenterprise data platforms.
• Lead end-to-end Databricks implementation, including architecture, development, deployment, and optimization.
• Define Databricks workspace architecture, clusterstrategies, security models, and operational standards.
• Design and developscalable data pipelinesusingDatabricks, Apache Spark, PySpark, SQL, andDelta Lake.
• Implement data ingestionframeworks supporting batchand real-timedata processing.
• Design Delta Lake architectures including:
  • Delta tables
  • Medallion architecture (Bronze/Silver/Gold layers)
  • Data quality frameworks
  • Schema evolution andoptimization
• Perform Databricks performancetuning:
  • Cluster optimization
  • Spark job optimization
  • Query tuning
  • Cost optimization
• Implement Databricks governanceand security using:
  • Unity Catalog
  • Access controls
  • Data lineage
  • Audit capabilities
• Lead migration projectsfrom legacy dataplatforms to DatabricksLakehouse.
• Define best practicesfor Databricks CI/CD, DevOps, andenvironment management.
• Collaborate with dataengineers, data scientists, analysts, and enterprisearchitects.
• Provide technical guidance, architecture documentation, and design reviews.

Skills & Experience

• Strong experience in dataengineering, big data, or solution architecture.
• Strong hands-onexperience withDatabricks Platform.
• Expert knowledge of:
  • Apache Spark
  • PySpark / Scala
  • Delta Lake
  • SQL
  • Data Lakehouse architecture
  • ETL/ELT development
• Experience designing anddelivering enterprise Databrickssolutions.
• Strong experience withcloud platforms:
  • Azure Databricks (preferred)
  • AWS Databricks
  • Google Cloud Databricks
• Experience with:
  • Databricks Workflows
  • Jobs orchestration
  • Notebooks
  • Repos
  • Cluster management
  • Unity Catalog

Preferred Skills

• Databricks Certified DataEngineer Professional /Databricks Certified Architect.
• Experience with:
  • MLflow
  • Databricks Machine Learning
  • Feature Store
  • Model deployment
  • MLOps
• Knowledge of streamingtechnologies:
  • Structured Streaming
  • Kafka
• Experience with datagovernance, compliance,and enterprise securityframeworks.

Key Competencies

• Strong Databricks architectureand implementation expertise.
• Ability to designscalableand cost-efficientLakehouse solutions.
• Strong troubleshooting andperformance optimizationskills.
• Ability to leadtechnical discussions withenterprise stakeholders.