Operational domain knowledge
Frame the real operating objective, process, measures, conditions and available decisions.
Data Engineering & Analytics Leadership · Mining Operational Performance
Find what constrains value.
Quantify the impact.
I lead and build data engineering, analytics and AI systems that connect operational performance to measurable value—combining operational context with AWS, Snowflake, Python, SQL, dbt, Airflow and decision-focused analytics.
What I do: lead the platform, stay close to the engineering and turn operational evidence into measurable decisions. Operational value remains the outcome.
Integrated capability system
Different lenses. One operational-value discipline.
No single technique explains operational performance. The capability comes from combining domain context with temporal, spatial and causal evidence—then turning that evidence into a decision and a measurable outcome.
Theory of Constraints
Identify the limiting part of the system and avoid optimising activity that cannot improve the whole.
Time-series diagnostics
Find changes, delays, cycles, anomalies and relationships across operational time.
Spatial analytics & GIS
Reveal how location, distance, routes, boundaries, terrain and spatial conditions influence performance.
Forecasting & ML
Estimate likely outcomes, detect patterns and test scenarios with uncertainty made visible.
Data engineering
Connect trusted operational, asset, spatial and enterprise data with quality and provenance.
AI & automation
Accelerate analysis, repeat reliable workflows and deliver insight at the point of decision.
Value quantification
Translate driver changes into production and business impact, with assumptions explicit and outcomes measurable.
Context+Constraint+Time+Place+Prediction+Trusted Data+Automation→Highest-value action
Hands-on data leadership
Leadership that stays close to the engineering.
I combine technical leadership with hands-on delivery: setting architecture, standards, governance and delivery direction while remaining capable of diagnosing performance problems, reviewing code, designing data models and building critical components.
Platform Direction
Architecture, roadmaps, technology choices and investment priorities connected to operational outcomes.
Engineering Delivery
Hands-on capability across Python, SQL, Snowflake, dbt, Airflow, AWS and serverless systems.
Operational Reliability
Testing, release controls, observability, performance, cost management and incident discipline.
Team Capability
Engineering standards, mentoring, vendor leadership, delivery planning and stakeholder alignment.
01Operational problem
→
02Data products & contracts
→
03AWS + Snowflake
→
04dbt + Airflow
→
05Governed semantic models
→
06Power BI + Analytics + AI
→
07Decision & value
Operational context
Mining first. Transferable discipline.
Experience grounded in mining and complex operations, supported by enterprise data and industrial systems.
$5MEstimated mining cost saving identified through operational analytics
75% → 1%Data release failures reduced through engineering and controls
4h → 30mEnterprise data release cycle reduced
$400k p.a.Expected saving from replacement enterprise data pipeline
Core capability
From operating constraint to highest-value action.
The work starts with the operation, its value drivers and the decision available. Data, analytics and AI strengthen the evidence chain from performance loss to quantified opportunity and action.
01 / OPERATIONS
Operational Context
Understand the operation, objectives, constraints and performance measures.
02 / DRIVERS
Value Drivers
Identify the operational drivers that influence throughput, utilisation, productivity, cost and value.
03 / DATA
Data Foundation
Connect operational, asset, geospatial and enterprise data with reliable engineering, quality and provenance.
04 / ANALYTICS
Temporal, Spatial & Constraint Analysis
Use time-series diagnostics, GIS, statistics, forecasting and appropriate AI to locate material losses, relationships, constraints and opportunities.
05 / DECISION
Decision Support
Compare scenarios and turn analysis into prioritised, evidence-based actions for operational leaders.
06 / VALUE
Impact & Value
Quantify the potential production and business impact, then define how realised outcomes will be measured.
Operation↓Performance Driver↓Data & Evidence↓Time + Space + Analytics / AI↓Decision↓Operational & Business Value
Value driver thinking
Performance metrics tell you what happened. Value drivers show where intervention matters.
This is an illustrative framework, not a universal mining equation. Definitions, causal relationships and value-driver structures differ between operations and must be validated against local context and evidence.
Outcome
Business Value
Measurable operational and financial outcomes.
Level 05
Production / Cost / Productivity
Level 04
Throughput / Rate / Yield
Level 03
Operating Time / Availability / Utilisation
Level 02
Delays / Constraints / Asset Performance
Evidence
Operational Conditions & Root Causes
Asset Intelligence
Asset performance is a value driver.
Reliability, condition monitoring, failure modes and inspection evidence help explain how asset condition contributes to production losses, operational risk and performance. This is a substantial application of the broader operational-performance approach—not a separate professional identity.
01 / ASSET
Asset & failure context
Operating regime, failure modes, consequences and criticality.
02 / EVIDENCE
Condition & operational data
Thermal, vibration, inspection, sensors and operating context.
03 / ANALYSIS
Diagnostics & predictive analytics
Rules and statistics first; machine learning where it adds reliable evidence.
04 / IMPACT
Operational consequence
Connect condition and failure risk to constraints, lost production and decisions.
Selected products & projects
Different problems. One decision discipline.
These projects show the capability applied across mining performance, geospatial assurance, personal forecasting and physical-asset intelligence.
Operational performance & value intelligence
Mining Decision Support
Enterprise mining analytics and compliance-to-plan insight used to identify performance drivers, constraints and measurable improvement opportunities.
Operational contextFrame measures around the operation, the available decision and the source of performance loss.
Quantified opportunityConnect operational drivers to production and business impact without hiding assumptions or constraints.
Decision outcomePrioritise the actions most likely to improve the operational result, then measure what changed.
Geospatial processing & assurance
VoxelData
Automated, evidence-based QA/QC and processing workflows for orthomosaic GeoTIFF handovers and downstream spatial products.
ArchitecturePython · AWS serverless · SAM · secure spatial-data workflows
Spatial + temporal decision product
Field Window
A personal photography-intelligence platform that translates weather, light, tide, location and equipment data into explainable field recommendations.
ArchitectureAWS Amplify · Cognito · forecast and location-data integration
Asset intelligence · Practical exploration
Asset Health Lab
Practical exploration of rotating equipment, failure modes, thermal and vibration evidence, data engineering and analytics—building industrial depth that supports broader operational intelligence.
Experience
Engineering leadership, grounded in delivery.
Experience leading data products, platforms, analytics, teams and vendors across mining and complex enterprises—while remaining technically engaged in architecture, performance engineering, data modelling and critical delivery.
Engineering
Python · SQL · dbt · Airflow · APIs
Platforms
AWS · Snowflake · Serverless architecture
Analytics
Power BI · DAX · Semantic models · Forecasting · AI
Delivery
Git · Automated testing · CI/CD · Monitoring · Governance
BHP — Global Operational Performance
Leads product delivery across operational performance insight, data engineering, analytics, visualisation and GenAI; previously Principal Data & Platform Engineer. Introduced engineering controls, source management and performance optimisation while coordinating team members, vendors and stakeholders.
CoreLogic — Data Operations & Commercial Research
Executive leadership across enterprise property data, data operations, commercial research and spatial analytics—alongside hands-on architecture for highly available SQL Server, replicated PostgreSQL and cloud data processing.
Fallon Solutions — Cloud Data Architecture
Designed decoupled AWS data platforms, serverless ingestion, governance, analytics, predictive modelling and operational decision support.
Earlier enterprise consulting
Database, data administration and technical consulting across Oracle, SQL Server and enterprise systems.
Working notes
Operational performance, data and industrial intelligence.
Writing and practical work across performance drivers, enterprise data, analytics, AI, asset intelligence, architecture and evaluation.
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Read note →Current direction
Lead the platform. Build the evidence. Improve the operation.
I combine hands-on data engineering with platform, team and delivery leadership to build reliable decision systems for mining and complex operations.
Let’s connect →