Databricks Architect

Level: Manager / Senior Manager

Location: Flexible

Practice: Data & Analytics / AI & Cloud Engineering

Role Overview

We are seeking a highly experienced Databricks Architect to lead the design and delivery of next-generation data and AI platforms for leading enterprise clients. This individual will be responsible for architecting scalable Lakehouse solutions, modernising data estates, and enabling advanced analytics, machine learning, and AI capabilities.

The successful candidate will combine deep technical expertise with strong consulting and leadership capabilities, helping clients unlock value from their data through modern cloud-native architectures.

Key Responsibilities

• Architect enterprise-scale Databricks Lakehouse platforms.
• Lead design and implementation of end-to-end data engineering, analytics, and AI solutions.
• Define data architecture standards, governance frameworks, and operating models.
• Design real-time and batch data processing solutions.
• Lead legacy modernisation and cloud migration programmes.
• Work closely with client executives and business stakeholders to shape strategic roadmaps.
• Provide architecture oversight and technical leadership throughout delivery.
• Support pre-sales activities, solution design workshops, and proposal development.
• Mentor engineers, architects, and consulting teams.

Required Experience

Manager

• 6+ years of experience in Data Engineering, Data Platforms, or Analytics Engineering.
• Hands-on Databricks implementation experience.
• Experience with Apache Spark and distributed data processing.
• Strong knowledge of cloud platforms (Azure, AWS, or GCP).
• Experience building scalable ETL/ELT frameworks.
• Strong consulting and stakeholder management skills.

Senior Manager

• 10+ years of experience delivering enterprise-scale data transformation programmes.
• Significant experience leading Databricks architecture engagements.
• Proven leadership of large, globally distributed delivery teams.
• Experience advising C-suite stakeholders on data and AI strategy.
• Track record in business development, solution sales, and practice growth.

Technical Skills

• Databricks Lakehouse Platform
• Apache Spark (PySpark, Scala, SQL)
• Delta Lake
• Data Engineering & Data Modelling
• MLOps and ML Lifecycle Management
• Streaming Technologies (Kafka, Event Hubs, Kinesis)
• Data Governance and Security
• Azure, AWS, or GCP
• CI/CD, DevOps and Infrastructure as Code

Preferred Certifications

• Databricks Certified Data Engineer Professional
• Databricks Certified Solutions Architect
• Azure Data Engineer Associate
• AWS Data Analytics Specialty
• TOGAF (desirable)

Key Competencies

• Cloud and data architecture leadership
• Executive stakeholder management
• Data and AI strategy development
• Commercial and business development skills
• Team leadership and mentoring

*This role will be a mixture of office work and client travel*

*Business level German is required*