Omar Alfarouk Abbas

Senior Analytics Engineer · Data Engineer · Finance Data Analyst

I build data platforms that regulators trust and engineers enjoy maintaining.

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About

Analytics Engineer with 5+ years. I spend most of my time in the space between raw data and a regulator's inbox — building pipelines that are automated, validated, and boring in the best way (no surprises at 3 AM).

Currently at Vision Bank (Saudi Arabia):

• Collaborating in PostgreSQL/Oracle → Google BigQuery migration with Google Professional Services
• Automating SAMA regulatory reporting end-to-end: schema discovery → dbt models → Airflow orchestration → validation frameworks → submission
• Building a Self-Service BI layer on Tableau so analysts stop asking me for ad-hoc queries

Previously shipped BI platforms at ZATCA (with Deloitte & PwC), TETCO, and Blueprint Technologies (Dubai).

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How I Think About Data Currently

Raw Source  →  Staging  →  Intermediate  →  Marts  →  BI / Regulatory Reports
   │              │              │              │              │
   │         dbt source     dbt models     Star Schema    Tableau / 
   │         freshness      + tests        Kimball        Looker /
   │         checks         + docs         modelling      Power BI
   │              │              │              │              │
   └──────── Airflow orchestrates the whole thing ────────────┘
                              │
                    BigQuery / Snowflake / Databricks
                    (the warehouse layer)

Opinions I hold:

• dbt tests are not optional — if it doesn't have not_null and unique, it's not production-ready
• Dimensional modelling (Kimball) still wins for analytics — wide tables are a code smell
• Regulatory pipelines need reconciliation at every hop, not just at the end
• If a dashboard takes more than 10 seconds to load, it's an engineering failure

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Impact

ETL Runtime            60+ min  →  5–10 min       ██████████████░░  80% faster
Dashboard Refresh      2+ hours →  under 5 min    ████████████████  95% faster
File Size              500 MB   →  under 100 MB   ████████████░░░░  79% smaller
Regulatory Accuracy    ————————————————————————    ████████████████  100%
Executive KPIs         ————————————————————————    ████████████████  100+ shipped

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Tech Stack

Data Engineering & Orchestration

Programming

BI & Visualisation

Cloud & DevOps

Regulated Domains

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Currently Exploring

learning_queue = {
    "deep_dive":    ["Apache Spark / PySpark", "Databricks", "Data Vault 2.0"],
    "leveling_up":  ["MLOps fundamentals", "Great Expectations (data quality)"],
    "studying":     "MSc Data Science — Rome Business School (2025–present)"
}

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📌 Featured Projects

Project	What It Does	Stack
🏦 regulatory-reporting-framework	End-to-end SAMA regulatory reporting: staging → transformation → validation → submission. Reconciliation checks at every hop.	dbt, Airflow, BigQuery, Python
🧱 dbt-dimensional-model	Sample dimensional model (Star Schema / Kimball) with staging, intermediate, and mart layers. Includes dbt tests, docs, and CI.	dbt, BigQuery, GitLab CI
🔄 airflow-orchestration-patterns	Production Airflow DAG patterns: sensor triggers, dynamic task mapping, failure alerting, SLA monitoring.	Python, Airflow, Docker
⚡ sql-performance-cookbook	Advanced SQL optimisation: CTEs vs subqueries, window functions, partition pruning, query plan analysis. Real examples from BigQuery + PostgreSQL.	SQL, BigQuery, PostgreSQL
📊 power-bi-optimization-toolkit	DAX refactoring patterns, data-model compression, incremental refresh configs. Cut dashboard refresh by 70–95%.	Power BI, DAX, SQL

Some repos contain sanitised examples inspired by production patterns — no proprietary data.

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Certifications

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Education

🎓 MSc Data Science — Rome Business School, Italy (2025 – Present)

🎓 BSc Mathematics & Computer Science — University of Gezira, Sudan (2014 – 2020)

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💬 I like talking about: dimensional modelling · dbt patterns · regulatory data pipelines · cloud migration war stories · why your dashboard is slow

📬 Reach me: mr.omarmoffed@gmail.com · LinkedIn · omaralfarouk.work