Senior Databricks Solution Architect

Unison Group; Veglio; On-site; EUR 90,000 - 120,000; Full time

Job summary

Unison Group is seeking a Senior Databricks Architect to design, implement, and optimize enterprise-scale data platforms on the Databricks Lakehouse Platform. You will lead architecture, development, deployment, and performance tuning across analytics teams.

The role requires deep expertise in Databricks, Spark, Delta Lake, and cloud platforms (Azure, AWS, GCP), plus governance, security, and data quality. You will collaborate with data engineers, data scientists, and enterprise architects to

Qualifications

• Deep expertise in Databricks architecture and lakehouse patterns.
• Hands-on experience with Spark, Delta Lake and PySpark/Scala.
• Proven ability to deliver enterprise-scale data platforms.

Responsibilities

• Design and implement enterprise Databricks Lakehouse solutions.
• Lead end-to-end Databricks deployments including architecture and optimization.
• Define workspace architecture, cluster strategies, security models, and governance.
• Develop scalable data pipelines using Databricks, Spark, PySpark/SQL, Delta Lake.
• Implement ingestion frameworks for batch and real-time processing.
• Lead migrations from legacy platforms to Databricks Lakehouse.
• Define CI/CD, DevOps practices for Databricks environments.
• Collaborate with data engineers, data scientists, analysts, and architects.

Skills

Databricks architecture

Apache Spark

PySpark/Scala

Delta Lake

SQL

ETL/ELT development

Cloud platforms

Data Lakehouse architecture

Data governance

Security model design

Tools

Databricks Platform

Azure Databricks

AWS Databricks

Google Cloud Databricks

Unity Catalog

Notebooks/Repos

Jobs orchestration

Job description

• ETL/ELT development
• Model deployment

We are seeking a Senior Databricks Architect to design, implement, and optimize enterprise-scale data platforms using the Databricks 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 architect Databricks Lakehouse solutions for large-scale enterprise data platforms
• Lead end-to-end Databricks implementation, including architecture, development, deployment, and optimization
• Define Databricks workspace architecture, cluster strategies, security models, and operational standards
• Design and develop scalable data pipelines using Databricks, Apache Spark, PySpark, SQL, and Delta Lake
• Implement data ingestion frameworks supporting batch and real-time data processing
• Design Delta Lake architectures including:
• Delta tables
• Medallion architecture (Bronze/Silver/Gold layers)
• Data quality frameworks
• Schema evolution and optimization
• Perform Databricks performance tuning:
• Cluster optimization
• Spark job optimization
• Query tuning
• Cost optimization
• Implement Databricks governance and security using:
• Unity Catalog
• Access controls
• Data lineage
• Audit capabilities
• Lead migration projects from legacy data platforms to Databricks Lakehouse
• Define best practices for Databricks CI/CD, DevOps, and environment management
• Collaborate with data engineers, data scientists, analysts, and enterprise architects
• Provide technical guidance, architecture documentation, and design reviews

Skills & Experience

• Strong experience in data engineering, big data, or solution architecture
• Strong hands-on experience with Databricks Platform
• Expert knowledge of:
• Apache Spark
• PySpark / Scala
• Delta Lake
• SQL
• Data Lakehouse architecture
• ETL/ELT development
• Experience designing and delivering enterprise Databricks solutions
• Strong experience with cloud 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 Data Engineer Professional / Databricks Certified Architect
• Experience with:
• MLflow
• Databricks Machine Learning
• Feature Store
• Model deployment
• MLOps
• Knowledge of streaming technologies:
• Structured Streaming
• Kafka
• Experience with data governance, compliance, and enterprise security frameworks

Key Competencies

• Strong Databricks architecture and implementation expertise
• Ability to design scalable and cost-efficient Lakehouse solutions
• Strong troubleshooting and performance optimization skills
• Ability to lead technical discussions with enterprise stakeholders