I'm Hammad Tariq, a Data & Automation Engineer with 5+ years on AWS, building production data platforms and the automation around them: ETL pipelines, cloud warehouses, backend APIs and AI features that cut cost and scale cleanly.
Hammad Tariq
Data & Automation Engineer
A robot-arm benchmark found GPT-6 Astra refused 2 of 100 hazardous instructions. The same gap applies to any LLM agent with write access to your data.
Tools of the trade
Trusted by teams at
Whether it's orchestrating ETL or modelling a cloud data warehouse, the focus is always scalability, observability and clean execution.
I build the AWS data layer a business runs on: ETL/ELT pipelines, cloud warehouses on Redshift and Snowflake, and migrations off creaking on-prem systems. My focus is the unglamorous part: whether the platform still holds up when real data gets messy at 2am. Recent work cut operating costs by up to 99% and turned hours of manual effort into seconds. The AWS-cost lessons from that work are in my guide to cutting an AWS Glue bill.
Orchestrated ETL/ELT with Dagster, dbt and Airflow, from raw ingestion to analytics-ready warehouses.
Data marts and warehouses on Snowflake, Redshift and BigQuery: modelled, governed and query-fast.
Dockerised, CI/CD-driven deployments on AWS with cost optimisation and observability baked in.
Idempotent pipelines, isolated failure domains and graceful degradation, built to survive real data.
Real systems with measured outcomes: the problem, the architecture, and the numbers that moved.
Re-platforming a tier-1 banking EDW onto a cloud-native AWS warehouse
Led the migration of a major retail bank’s on-premises Enterprise Data Warehouse from Sybase to Amazon Redshift on AWS, re-engineering 800+ stored pro…
A 3-tier AWS Glue pipeline for assessment, measurement & analysis data
Built a 3-tier data architecture on AWS for an environmental-solutions provider, using AWS Glue, S3, Redshift, Lambda and PySpark to lift data-process…
Re-architecting on-prem ETL into AWS for 80% better resource utilisation
Led a data-warehouse migration to AWS for a pan-African financial-services group, moving 20–30 ETL scripts and stored procedures onto Glue, Redshift a…
AI Cost Attribution & Real-Time Outage Monitoring from Shared Provider Spend
Restores per-application cost visibility from a single shared AI invoice. A near-zero-touch SDK captures durable usage “receipts”, and invoice-anchore…
AI-Powered Multilingual OCR & Document Intelligence
Converts scanned PDFs and photographed forms into clean, structured Markdown across 10+ languages, including hard scripts like Urdu, Arabic and Amhari…
Hands-off SFTP-to-analytics for daily sales & stock data
An automated ELT pipeline that detects distributor files landing on SFTP, validates and homologates them, and lands analytics-ready data in S3 for rea…
Practical deep dives on data engineering, ETL and analytics: the decisions and the numbers behind real work.
What it costs to automate a manual process, from a real build: where the money actually goes, what the estimate missed, and how to size the payback first.
Mask PII in an S3 data lake at the ingest boundary: deterministic hashing that keeps joins working, Glue detection, Lake Formation filters, KMS and erasure.
S3 small files problem: why your data lake got slow and pricey, how to spot it in one query, and how compaction and 128 MB–1 GB files fix it.
Small, browser-based utilities I built. No signup, and nothing leaves your browser.
A few words from people I've delivered for.
“Skilled, flexible, and fast. Would hire Hammad again.”
“Excellent communication and amazing work with great execution.”
Three ways to engage: own the technical direction, answer one hard question, or run a project to the finish line.
Whether that is ongoing technical ownership, one independent read on a problem, or someone to run the project. Let's scope it — I reply within one business day.