Databricks Architect (Data Engineering)
Description
About the role
We are looking for an experienced Databricks Architect to design and lead modern data platforms built on the Databricks ecosystem. In this role you will define architecture standards, establish engineering best practices, and support development teams in delivering scalable, secure and high-performing data solutions.
Responsibilities
Design end-to-end Data Lakehouse architectures based on Databricks
Define data platform architecture, integration patterns and governance standards
Lead architecture decisions around ETL/ELT, batch and streaming data processing
Design scalable solutions using Delta Lake, Unity Catalog and Medallion Architecture
Collaborate with Data Engineers, Data Scientists, Architects and business stakeholders
Define security, data governance and access management strategies
Optimize platform performance and cloud costs
Support CI/CD implementation and Infrastructure as Code practices
Review solution designs and mentor engineering teams
Drive adoption of modern Data Engineering best practices
Requirements
7+ years of experience in Data Engineering
3+ years of hands-on experience with Databricks
Strong expertise in Apache Spark (PySpark and/or Spark SQL)
Excellent knowledge of Delta Lake and Lakehouse Architecture
Experience designing enterprise-scale data platforms
Strong understanding of Medallion Architecture
Experience with Unity Catalog and data governance
Experience with cloud platforms (Azure, AWS or GCP)
Knowledge of orchestration tools (Azure Data Factory, Airflow, Databricks Workflows or similar)
Experience with CI/CD pipelines and Git-based development
Strong SQL and Python skills
Excellent communication and stakeholder management skills
Fluent English
Nice to have
Databricks certifications
Experience with dbt
Experience with Kafka or other streaming technologies
Terraform or other IaC tools
Experience designing AI/ML-ready data platforms
German language level C1/C2 or native