Our data lives in separate tools.
Bring marketing spend, orders, subscriptions, and operational data into a useful reporting layer.
Data engineering & automation consulting
Turn messy data and manual workflows into reliable systems.
I connect business systems, automate reporting and operations, and build practical dashboards and interfaces—from a focused first delivery to deeper data and backend work.
Where I can help
Start with the problem your team needs solved.
We keep rebuilding the same reports.
Automate recurring exports, Sheets updates, and file processing with checks around the output.
Our dashboards show different numbers.
Trace the inputs, joins, and metric definitions so the discrepancy can be explained and corrected.
Our integration keeps failing.
Make authentication, syncs, webhooks, and recovery part of a controlled workflow.
Services
A useful output. A dependable system behind it.
01
Marketing & Business Reporting Systems
Connect marketing, ecommerce, subscription, and operational data so your team can answer business questions without rebuilding reports by hand.
Explore the service 02BigQuery & Dataform Consulting
Make a difficult BigQuery warehouse easier to trust and maintain: clear models, dependable transformations, and controlled recovery when inputs change.
Explore the service 03API & Workflow Automation
Turn a manual workflow or fragile integration into a controlled process, with validation, recovery, and a practical interface for the people using it.
Explore the serviceConnect sources → validate and model → automate → expose useful reporting or operational interfaces.
AI access to your data
Your business data, available in Claude or ChatGPT.
I prepare the reporting data and connect the right interface so your team can explore defined business questions alongside its dashboards and reports. We can start with existing data or connect the missing sources first.
Explore AI data accessStart with a question.
How did spend and new customers compare by channel? What changed this week? What do the latest operational records show?
Defined metrics → authenticated access → useful answers.
Selected work
The system behind the useful output.
Marketing Data Platforms
Marketing Data & Campaign Analytics Platform
Advertising APIs, BigQuery reporting layers, recovery workflows, and campaign analysis behind a marketing analytics product.
Google Sheets Automation
Google Sheets and Apps Script Reporting Automation
Automating recurring Sheets updates and document/report outputs while keeping configuration and validation understandable for the team.
Backend & Connected Devices
AWS Connected-Device Backend & Telemetry
Backend and telemetry engineering within an existing connected-device product: APIs, aggregation, recovery, and cloud performance work.
Working together
Start focused. Build on what works.
- 01
Find a useful starting point
Share the questions to answer or the workflow to improve. A short conversation establishes the first output and the constraints that matter.
- 02
Agree scope and access
Receive a written scope covering deliverables, source access, definitions, exclusions, price, and timing. Existing tools stay in the picture where they work.
- 03
Build, validate, and hand over
Review working outputs against source data and agreed examples. Get operating notes, limitations, and a practical handoff.
- 04
Expand when needed
Add sources, deeper modeling, recovery, or a custom interface as the business need becomes clear.
Client feedback
Engineering, communication, and handoff.
“Ahmad is an exceptional engineer. He solved really hard problems that required a lot of iteration and testing, and was super helpful with the hand-off to our internal team.”
“Ahmed is very competent and easy to work with. He has great communication and technical skills. He went above and beyond to deliver excellent work. I highly recommend him.”
“Ahmad was great to work with. Always prompt and did everything that was asked of him. Readily available and trustworthy.”
“Great guy with extensive knowledge in BigQuery and Data Looker. Has a remarkable ability to tackle complex tasks and go above and beyond to deliver great results.”
Insights
Practical notes from building the systems.
Marketing Data
Scoping a Useful First Version of Automated Business Reporting
Choose initial questions, define CAC and customer value, connect accessible sources, and agree a useful first reporting output without hiding its limitations.
Analytics Engineering
Recomputing BigQuery Reporting Models with Dataform After Inputs Change
Changed historical dates, attribution settings, refresh checkpoints, and safe replacement: practical recomputation design for BigQuery reporting models.
Marketing Data
Connecting BigQuery to Claude: Prepare the Reporting Layer Before MCP
A practical example of connecting AI to business reporting: shared metric definitions, scoped access, freshness, and answer checks over BigQuery data.
Common questions
A clear starting point.
Can we start with a small reporting or automation project?
Yes. A first delivery can focus on a defined set of questions, accessible sources, and one useful output. Larger modeling or integration work follows when needed.
Do you work beyond marketing reporting?
Yes. My experience includes API integrations, backend and cloud workflows, payments/subscriptions, connected-device systems, and telemetry alongside marketing data engineering.
Do we need a new warehouse or custom dashboard?
It depends on the problem. Existing Sheets, connectors, reporting tools, or backend systems may be enough. A warehouse or custom interface is useful when the requirements justify it.
Can our team explore the data through Claude or ChatGPT?
Yes. I can prepare reporting data or connect existing APIs through an authenticated interface for the selected AI client. My work includes a BigQuery serving layer for marketing insights and a Claude/MCP integration with scoped access to application and telemetry data. We agree the supported questions, metric definitions, account configuration, and access before building.
How are cost and delivery timing agreed?
After a short conversation, the written scope specifies deliverables, access, assumptions, exclusions, price, and timing. A deadline is agreed around the actual scope and source availability.
Let’s talk
Find a useful starting point.
Share the questions you need answered or the workflow you want to improve. We can start with a focused delivery and expand when needed.
Book an introductory call ↗Opens Calendly in a new tab.
What happens next
- A short conversation about the first useful output and relevant systems.
- A written scope with deliverables, access, assumptions, price, and timing.
- An agreed build, validation, and handoff.
Prefer email? ahmadhumayun.k@gmail.com