Platforms built inside enterprise programmes.

Customer analytics on one platform, and a way to onboard new data teams without a project each time.

• Built customer-analytics pipelines on Airflow, Google Cloud, Dataproc and BigQuery
• Architected a central Databricks platform for fast onboarding of data sources and product teams
• Streaming ingestion with Spark Structured Streaming and Kafka
• A Unity Catalog permissions model for engineering teams and service principals, expressed in Terraform, plus reusable CI/CD template components for standardised deployment

• Databricks
• Unity Catalog
• PySpark
• Kafka
• Airflow
• GCP
• Terraform

Company-wide data democratisation, including the SAP estate.

• Designed and built the platform on Azure and Databricks
• Analytics solutions for supply-chain and product-lifecycle domains
• SAP ERP master and transactional data integrated
• Declarative Asset Bundles, a data governance concept and a CI/CD concept adopted across teams

• Azure Databricks
• Unity Catalog
• SAP ERP
• PySpark
• Azure Data Factory
• Asset Bundles

An enterprise data lake and a self-service science environment used across the group.

• Built and operated the corporate lakehouse
• A secure, reusable Data Science Lab deployed for 200+ internal clients
• Automated infrastructure and CI/CD
• Data-integration programmes including a B2B industry platform and customer analytics

• Azure Databricks
• Terraform
• Azure DevOps
• Azure ML
• SAP ERP
• Kafka
• Power BI

Analytics over billions of records a day, in batch and in real time.

• Architected and operated the big-data infrastructure
• Built a data-management framework on DataOps principles
• DWH modelling and query optimisation
• Advanced analytics on very large datasets in both batch and streaming

• Spark
• Scala
• Kafka
• Hadoop
• Impala
• Postgres
• Spring Boot

One warehouse from five disconnected systems.

• Architected the corporate lakehouse on Azure Databricks and Airflow
• Consolidated SAP ERP, CRM, web analytics and an in-house ERP for analytics
• A streaming proof of concept for event ingestion
• Comprehensive unit and integration test coverage across PySpark and Airflow code

• Azure Databricks
• Airflow
• SAP ERP
• Spark Structured Streaming
• pytest

A cloud data-lake concept the security team would actually approve.

• Cloud lakehouse concept on Azure Databricks with a strong DevOps focus
• Identity, storage and pipeline design
• Infrastructure as code

• Databricks
• ADLS Gen2
• Azure AD
• Terraform
• GitLab