About This Service
Data Engineering — ETL Pipelines, dbt & Airbyte for UAE Businesses
I build modern ELT data pipelines that pull everything your business generates — POS transactions, CRM contacts, ad-platform spend from Meta and Google, accounting exports, web analytics — into a single warehouse that becomes your one source of truth. For trading companies, retailers, and clinics across Dubai, Abu Dhabi, and Sharjah, the typical starting point is painful: numbers live in five systems, monthly reporting means days of copy-paste, and no two spreadsheets agree on what revenue was.
The stack is deliberately standard and open: Airbyte (or Fivetran-style managed connectors) handles extraction and loading on a schedule, the warehouse is BigQuery, Snowflake, or plain Postgres depending on your data volume and budget, and dbt handles the transformation layer — tested, version-controlled SQL models that turn raw loads into clean tables your analysts and dashboards consume. Every dbt model ships with tests (uniqueness, not-null, referential integrity), so when a source system sends garbage, the pipeline tells you instead of silently feeding wrong numbers into board reports.
Where schedules get complex — dependencies between syncs, backfills, alerting — I add an orchestrator such as Airflow or Dagster. For most free-zone and mainland SMEs in the UAE, though, the goal stays simple: every morning, one warehouse holds yesterday's complete, reconciled picture of the business in AED.
What's included
- Source connectors — Airbyte connections to your POS, CRM, ad accounts, and databases on automatic schedules
- Warehouse setup — BigQuery, Snowflake, or Postgres provisioned and structured for analytics workloads
- dbt transformation layer — Version-controlled SQL models turning raw loads into clean, documented marts
- Data quality tests — dbt tests on every model so bad source data raises an alert, not a wrong report
- Orchestration & alerting — Airflow or Dagster where dependencies demand it, with failure notifications
- Lineage & docs — Generated dbt documentation showing exactly where every number comes from
How it works
- 1Source inventory
We list every system holding business data — POS, CRM, ads, accounting — and define the questions the warehouse must answer.
- 2Extract & load
Airbyte connectors are configured and the first historical sync lands your raw data in the warehouse.
- 3Model with dbt
I build staging and mart models with tests — revenue, customers, inventory — reconciled against your existing reports so the numbers are trusted.
- 4Schedule & hand over
Daily syncs and model runs go on autopilot with alerting, and your team gets the dbt repo, docs, and a walkthrough.
Why work with me
| With me | Typical agency | |
|---|---|---|
| Open-source stack you can self-host later | Proprietary lock-in | |
| Numbers reconciled against your old reports | ||
| Every model tested and documented in dbt | Undocumented SQL | |
| Warehouse running cost transparency | Estimated upfront in AED | Discovered on the invoice |