Our client is a leading SAP consulting and digital transformation partner committed to delivering innovative, high-impact solutions across enterprise analytics, cloud, and intelligent business platforms.
As enterprises modernize their data landscapes, the role of traditional data warehousing is rapidly evolving into scalable cloud-native Data Lakehouse architectures. Client is expanding its modern data engineering capabilities to help customers integrate enterprise data from SAP and non-SAP ecosystems, build advanced analytics platforms, and enable future-ready AI-driven solutions.
We are looking for an accomplished Databricks Lakehouse Architect / Cloud Data Engineering Leader who can play a key role in this transformation journey — designing modern data platforms, leading cloud data engineering initiatives, and bridging enterprise analytics with next-generation technologies.
The ideal candidate will combine strong hands-on expertise in Databricks, Spark/PySpark, Delta Lake, and Azure/AWS cloud platforms with the ability to engage customers, architect solutions, guide engineering teams, and drive successful delivery.
Role Overview:
We are looking for a hands-on Data Engineering leader who can architect modern cloud data platforms using Databricks Lakehouse and lead solution design, delivery, and engineering teams. This role requires strong technical ownership rather than a pure people management background.
Key Responsibilities:
• Architect scalable Data Lakehouse platforms
• Own solution design, estimation, architecture reviews and client discussions
• Build and optimize enterprise data pipelines
• Provide technical guidance to data engineering teams
• Establish best practices around performance, governance and architecture
Must Have - Databricks Architecture:
• Databricks Lakehouse design
• Delta Lake implementation
• Apache Spark / PySpark engineering
• Medallion architecture (Bronze/Silver/Gold layers)
• Data pipeline optimization
• Unity Catalog and data governance exposure
Cloud Platform Expertise (depth in one required):
Microsoft Azure:
• Azure Databricks
• Azure Data Factory (ADF)
• Azure Data Lake Storage (ADLS)
• Azure Synapse Analytics
OR
Amazon AWS:
• Databricks on AWS
• Amazon S3
• AWS Glue
• Redshift
• Athena
Good to Have:
• Snowflake
• ML Engineering exposure
• Cloud/Data Engineering certifications
Ideal Candidate:
A hands-on architect who can talk to customers, design solutions, estimate projects, guide engineers and review architecture while helping build a modern Data Engineering practice.