Databricks Lead Engineer

Overview

In this role you will drive client-focused data engineering initiatives, building scalable pipelines and lakehouse architectures. You will collaborate with solution architects, data engineers, and analytics leaders to deliver Databricks-based, governed data solutions. You’ll work across ingestion, transformation, modelling and governance to meet client needs and accelerate data-driven outcomes. This is a chance to shape enterprise data platforms at a global technology services leader and contribute to responsible innovation. You will thrive by aligning technical delivery with client goals and best practices in a fast-paced, cross-functional environment.

Responsibilities

• Client engagement and delivery
• Data pipeline development (batch and streaming)
• Databricks and lakehouse architectures
• Data modelling and optimisation (Delta Lake, Medallion architecture)
• Collaboration and best practices
• Quality, governance and security

Key requirements

• Proven data engineering and pipeline development on Databricks and cloud-native platforms
• Strong consulting values with client-facing collaboration
• Hands-on data lifecycle expertise (ingestion, transformation, modelling, governance, consumption)
• Strong problem-solving, analytical, and communication skills
• Experience leading or mentoring teams of engineers for scalable data solutions
• 5–8 years in data engineering/warehousing/architecture; 3+ years with Databricks
• University degree; MSc/BS preferred
• Databricks certifications desirable

• excellent communication
• collaboration
• problem-solving
• Databricks platform (Spark/PySpark/Scala, Delta Lake, Unity Catalog, MLflow)
• ETL/ELT tools (DBT, Matillion, Talend)
• SQL and Python

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