Melbourne-based Business Intelligence and Operations Analyst with 15+ years across data, supply chain and operations, focused on delivering clear, dependable insight through thoughtful analysis and well-designed reporting. My professional experience is in SQL and Tableau, applied most recently at NEC Australia, where I combine analytical discipline with practical operational understanding to support sound decision-making. I continue to deepen my skills through the project portfolio below, where I've built end-to-end analytics projects in dbt, Power BI and SQL, applying dimensional modelling, star schema design and ETL pipelines. These projects reflect a continuous, hands-on learning ethos.

Tightly scoped, single-theme builds — each project goes deep on one core skill.

• Focused Build 1 — operations-analytics-dbt-tableau-project — dbt testing + macros depth on the AdventureWorks distribution slice. PostgreSQL → dbt (custom generic tests, dbt-utils + dbt-expectations, reusable macro, incremental model, snapshot — 155 tests green) → live three-dashboard Tableau Public workbook.
• Focused Build 2 — analytics-tsql-adf-project — T-SQL depth on real Jira issue data. Jira REST API → Azure Data Factory (paginated raw JSON, no flattening) → Azure SQL → T-SQL star schema (OPENJSON shred, MERGE upserts, stored procedures, presentation views) → 3-page Power BI dashboard with 25 documented DAX measures.
• Focused Build 3 — health-analytics-fabric-project — Microsoft Fabric end-to-end on AIHW MyHospitals open data. AIHW REST API → Fabric Data Pipeline → Lakehouse medallion (Bronze → Silver → Gold) → PySpark star schema → Direct Lake + Import Power BI 3-page dashboard with 22 documented DAX measures.

Larger architecture builds across cloud warehouse, lakehouse and orchestration stacks.

• End-to-End Platform 1 — cdc-nt-gtfs-project — two NT GTFS feeds (Darwin + Alice Springs) → Python ingestion → PostgreSQL → dbt (Kimball star) → 4-page Power BI dashboard. Multi-feed surrogate keys resolving cross-feed ID collisions; Kimball modelling foundation.
• End-to-End Platform 2 — retail-demand-forecasting-project — production-grade retail demand-planning pipeline. M5 Forecasting (Kaggle/Walmart) → Azure SQL → Python extract → Snowflake → Airflow (Docker) → dbt (Kimball star) → Snowflake Cortex forecast → 5-page Power BI dashboard.
• End-to-End Platform 3 — financial-analytics-lakehouse-project — AWS-native data lakehouse on SEC EDGAR XBRL fundamentals for the S&P 100. Direct-to-S3 raw → dbt-athena on Apache Iceberg → AWS Step Functions orchestration → 6-page Power BI analytical report with univariate revenue forecasting.

• pheluciam.github.io — 2023 self-directed learning portfolio. Background only; see the projects above for current work.

• SQL & modelling: PostgreSQL, T-SQL, Snowflake, dbt, dbt-athena, dimensional modelling, Data Vault 2.0
• Pipelines: Airflow, Azure Data Factory, AWS Step Functions, Microsoft Fabric Data Pipelines, PySpark, Python (pandas), Docker
• BI & reporting: Power BI (Import + Direct Lake), Tableau (live Tableau Public workbook)
• Cloud / lakehouse: AWS (S3, Glue, Athena, Step Functions, Lake Formation), Azure (Data Factory, Azure SQL), Microsoft Fabric (OneLake, Lakehouse, Delta), Apache Iceberg, medallion architecture

NEC Australia (BI Analyst & Programmer, Sept 2023 – Mar 2026). Prior 15+ years across operations and supply chain analytics — Harding's Hardware, Alex Makes Meals, Spartan School Supplies.

Open to roles in Melbourne's north-eastern, eastern and south-eastern suburbs.