Senior Databricks Solution Architect

Unison Group; Veglio; On-site; EUR 120,000 - 170,000; 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. You will lead end-to-end Databricks implementations and shape architecture, security, and governance.

You will collaborate with data engineers, data scientists, and enterprise architects to define best practices for CI/CD, workflows, and cost optimization while delivering scalable, secure data solutions across cloud platforms.

Qualifications

• Experience in data engineering and enterprise data platforms.
• Hands-on Databricks platform experience.
• Expert knowledge of Spark, Delta Lake, and SQL.
• Proven ability to design scalable Lakehouse architectures.

Responsibilities

• Design and architect Databricks Lakehouse solutions for large-scale platforms.
• Lead end-to-end Databricks implementations.
• Define workspace architecture, cluster strategies, security models, and governance.
• Develop scalable data pipelines using PySpark, SQL, and Delta Lake.
• Implement data ingestion frameworks for batch and real-time processing.
• Guide migration from legacy platforms to Databricks Lakehouse.
• Champion CI/CD, DevOps, and environment management for Databricks.

Skills

Data engineering

Big data

Solution architecture

Databricks Platform

Apache Spark

PySpark/Scala

Delta Lake

SQL

Lakehouse architecture

ETL/ELT development

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 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