You will get an end-to-end fully automated data pipeline & ETL for your BigData Projects
Project details
I'm offering an end-to-end fully automated data pipeline platform based on latest workflow management technologies. I can connect to cloud and on-premises datastores, extract, transform and load data to your datalake. I can build specific ETLs following your business requirements. My offer includes my commitment to understand your business in order to deliver best value.
My experience in DevOps can help you to minimize human errors in executing repeatable ETLs task, I can even intervene in building final AI Model to profit maximum from your data.
My experience in DevOps can help you to minimize human errors in executing repeatable ETLs task, I can even intervene in building final AI Model to profit maximum from your data.
Database Type
MySQL, MS SQL, SQLite, PostgreSQL, MongoDB, Teradata, Azure Cosmos DBWhat's included
| Service Tiers |
Starter
$1,500
|
Standard
$4,000
|
Advanced
$10,000
|
|---|---|---|---|
| Delivery Time | 10 days | 20 days | 30 days |
Number of Revisions | 1 | 4 | 9 |
Query Debugging | |||
Query Optimization | - | ||
Query Scheduling | |||
Query Analysis | - | ||
Source Code |
4 reviews
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GD
Gus D.
Mar 22, 2021
API to pull YouTube Social Media Data
LM
Luke M.
May 4, 2018
Python Pandas Analyst
Thanks for your work, Adil. It was a hard job!
MB
Marcel B.
Jan 19, 2017
Wanted: Data Scientist for Ranking Features (45 min)
Did a great job.
vk
vincent k.
May 29, 2016
Python - pandas data wrangling
good work overall
About Adil
Agentic AI expert | Devops | Automation | Full Stack
Paris, France - 6:01 am local time
I don't start from zero on your project. I bring my own AI delivery setup: an orchestration layer I built and run daily, where requirements become structured specs, acceptance criteria, and task breakdowns, then a fleet of coding agents implements each task against your codebase. Automated gates—tests, lint, security scan, review checklist—decide what's allowed through. Changes land as reviewable PRs and move to production via your existing CI/CD. Every step is logged, so when you do want to look, you can see exactly what was decided and why. Your code stays in your perimeter: on-prem or your cloud, your own model credentials, agent-agnostic (Claude Code, Codex, OpenCode).
That setup is why I move faster than a team twice my size—and why the output holds up. It works because I've spent 13 years on the unglamorous half: Kubernetes, OpenShift, CI/CD, observability, enterprise data platforms. That's the difference between an AI demo and a delivery flow your team can rely on Monday morning. I don't sell AI experiments. Humans stay at the requirement and review level; the machine handles everything in between.
Built and proven in regulated environments—energy, public sector, banking—where code can't leave the perimeter and every change needs a trail.
Agentic AI & automation: Claude SDK, Claude Code, MCP, LangGraph, n8n, and all similar tools.
DevOps platfoms: Kubernetes, OpenShift, CI/CD, observability
Data platforms: Cloudera, Dremio, Dataiku, Power BI
Tell me the outcome you want. I'll tell you straight whether this flow fits your case—and if it does, I'll build it.
Steps for completing your project
After purchasing the project, send requirements so Adil can start the project.
Delivery time starts when Adil receives requirements from you.
Adil works on your project following the steps below.
Revisions may occur after the delivery date.
Design the Data Model (if not provided)
Design the ETL/workflow