Senior Databricks Solution Architect

UNISON Group; Romanina; On-site; EUR 90,000 - 150,000; Full time

Job summary

UNISON Group seeks a Senior Databricks Architect to design, implement, and optimize enterprise-scale data platforms using the Databricks Lakehouse Platform. You will lead architecture, development, deployment, and performance tuning across hybrid cloud environments.

You will define workspace architecture, security models, and CI/CD practices while guiding data engineers, scientists, and analysts to deliver scalable, cost-efficient solutions.

Qualifications

• Strong hands-on experience with Databricks Platform.
• Expert knowledge of Apache Spark, PySpark/Scala, Delta Lake, SQL, and data lakehouse architecture.
• Experience designing and delivering enterprise Databricks solutions.
• Strong experience with cloud platforms (Azure Databricks preferred, AWS/GCP also).
• Proficiency with Databricks Workflows, Jobs orchestration, Notebooks, Repos, and cluster management.
• Knowledge of data governance and security frameworks (Unity Catalog).

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, Apache Spark, PySpark, SQL, and Delta Lake.
• Implement data ingestion frameworks for batch and real-time processing.
• Lead migrations from legacy platforms to Databricks Lakehouse.

Skills

Databricks Platform

Apache Spark

PySpark/Scala

Delta Lake

SQL

Data Lakehouse

ETL/ELT

Cloud platforms

Workflows/Orchestration

Unity Catalog

Tools

Databricks Platform

Apache Spark

PySpark

Scala

Delta Lake

SQL

Azure Databricks

AWS Databricks

Google Cloud Databricks

Databricks Workflows

Repos

Notebook

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.