Business Intelligence, Data & Analytics Specialist.

Cloud & Platform Infrastructure


  • Google Cloud Platform (BigQuery, cloud data pipelines)
  • Amazon Web Services (data and analytics workloads)
  • Proxmox
  • Hybrid and multi-platform architectures


Cost, security, and operational considerations

Data Engineering & Integration


  • Enterprise integration using Informatica, DataStage, and Matillion
  • Apache Airflow
  • Python + FastAPI (data pipelines, automation, analytics support)
  • ETL / ELT design and orchestration
  • Enterprise and cloud-native data pipelines


Data quality and validation frameworks

Databases & Data Platforms

  • Microsoft SQL Server
  • PostgreSQL, MySQL
  • BigQuery
  • Vertica
  • Netezza
  • Hadoop ecosystem (HDFS, Hive, Impala)
  • Redis

Approach to Technology

Technology choices should serve architecture, clarity, and long-term maintainability. My experience spans traditional enterprise platforms, modern cloud-native systems, and emerging AI-enabled architectures.

I focus on selecting and combining technologies pragmatically—based on suitability, risk, compliance, and operational realities—rather than trends or vendor preference.

Data & Analytics Foundations


  • SQL (enterprise-scale analytical and transactional systems)
  • Data modelling (conceptual, logical, physical)
  • Analytical and semantic layer design
  • Performance tuning and optimisation


Extensive experience across financial services, analytics platforms, and large-scale data environments.

Business Intelligence & Visualisation


  • MicroStrategy (long-term enterprise BI delivery)
  • Looker
  • Power BI
  • Tableau
  • Sisense + Zoho Analytics


Executive and operational reporting design

Technology is a means, not the outcome.

My focus is on choosing and combining tools that support clarity, compliance, and long-term value—while avoiding unnecessary complexity and lock-in.

Technology & Platforms

Security, Governance & Compliance


  • Collibra, Alation, Atlan, Atlas
  • Data governance frameworks (DAMA-aligned)
  • Data quality management
  • Privacy and regulatory alignment (GDPR, NIS2)
  • Secure-by-design data architectures

Architecture & Operating Environment


  • TOGAF-informed architecture practices
  • Linux and Windows environments
  • Virtualisation and infrastructure platforms
  • Open-source–first and vendor-neutral design

AI, Advanced Analytics & Automation


  • Tensorflow, n8n
  • AI implementation and automation with governance
  • Data preparation and feature design for ML
  • Responsible AI adoption in regulated environments
  • Integration of AI outputs into analytics and business workflows