You will get production ready ETL pipeline or dbt data model
Project details
Turn messy, scattered data into clean tables your team can trust. I build production-ready ETL pipelines and dbt data models that take raw data from files, APIs, databases, or ad platforms and deliver it structured, deduplicated, and analytics-ready.
I'm a data engineer working across AWS and GCP. Recent work:
• Meta Ads pipeline (PySpark + Apache Hudi) feeding a growth team's daily dashboards — star-schema modeling, SHA-256 deduplication
• dbt + BigQuery analytics on 99K+ orders — 7 staging models, 6 marts, 28 data-quality tests
• Real-time Kafka + PySpark streaming pipeline into PostgreSQL
What you get:
• A pipeline or dbt project built for your data and destination (BigQuery, PostgreSQL, Snowflake, S3)
• Clean transformations with deduplication, validation, and schema-drift handling
• Clear documentation, plus code you fully own — no lock-in
I document every decision before I build, handle messy or schema-shifting data instead of pushing it back to you, and reply within 24 hours.
Not sure which tier fits? Message me with your data and goal and I'll tell you what's realistic before you order.
I'm a data engineer working across AWS and GCP. Recent work:
• Meta Ads pipeline (PySpark + Apache Hudi) feeding a growth team's daily dashboards — star-schema modeling, SHA-256 deduplication
• dbt + BigQuery analytics on 99K+ orders — 7 staging models, 6 marts, 28 data-quality tests
• Real-time Kafka + PySpark streaming pipeline into PostgreSQL
What you get:
• A pipeline or dbt project built for your data and destination (BigQuery, PostgreSQL, Snowflake, S3)
• Clean transformations with deduplication, validation, and schema-drift handling
• Clear documentation, plus code you fully own — no lock-in
I document every decision before I build, handle messy or schema-shifting data instead of pushing it back to you, and reply within 24 hours.
Not sure which tier fits? Message me with your data and goal and I'll tell you what's realistic before you order.
Data Tool
PythonWhat's included
| Service Tiers |
Starter
$150
|
Standard
$400
|
Advanced
$900
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 10 days |
Number of Revisions | 1 | 2 | 3 |
Number of Graphs/Charts | 0 | 0 | 0 |
Number of Variations | 0 | 0 | 0 |
Data Source Connectivity | - | - | - |
Web Embedding | - | - | - |
Interactive/Animated Visuals | - | - | - |
Optional add-ons
You can add these on the next page.
Additional Revision
+$30
Data Source Connectivity
(+ 2 Days)
+$60
Airflow scheduling & orchestration
(+ 2 Days)
+$100
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MN
Muhammad Jamal N.
May 19, 2026
Python API Automation Framework — Pytest + Requests (Pet/REST API) — Showcase Project
Thanks Ammad for completing the project before time while maintaining quality work. Definitely will hire you in future. Goodluck
About Ammad
Data Engineer | PySpark, dbt, Airflow, BigQuery | AWS & GCP Pipelines
Lahore, Pakistan - 11:07 am local time
Recent production work:
• Meta Ads → BigQuery/PostgreSQL pipeline (Airbyte → S3 → PySpark + Apache Hudi) with SCD2 dimensional modeling, SHA-256 deduplication, and late-arriving attribution handling.
• dbt + BigQuery + Looker Studio analytics on 99K+ orders — 7 staging models, 6 marts, 28 data-quality tests, 4-page dashboard.
• Real-time Kafka + PySpark streaming pipeline running 9 concurrent queries with 4 windowed aggregations into PostgreSQL.
• Full AWS data platform on Terraform + EKS + EMR-on-EKS + Airflow with CI/CD.
How I work: I document every architectural decision before I build — scope, schema, and tradeoffs written down first — so downstream teams know exactly what they're querying. You get async-friendly updates on US/EU hours and pipelines that don't silently break on schema drift or duplicate events.
Core stack: Python, PySpark, SQL, Apache Airflow, dbt, Apache Hudi, Apache Kafka, AWS (S3, Glue, EMR, EKS, Athena), GCP/BigQuery, PostgreSQL, ClickHouse, Snowflake, Docker, Terraform, Looker Studio. Focus: ETL/ELT pipelines, dimensional modeling, data warehousing, streaming, and marketing analytics.
If you're building a data pipeline or need messy data turned into something your team can trust, send me the brief — I reply within 24 hours.
Steps for completing your project
After purchasing the project, send requirements so Ammad can start the project.
Delivery time starts when Ammad receives requirements from you.
Ammad works on your project following the steps below.
Revisions may occur after the delivery date.
Scope & confirm the build
I review your data source and goal, then confirm exactly what gets delivered — tables, transformations, and destination — so we're aligned before any code is written.
Build the pipeline
I build your ETL pipeline or dbt models — connecting to your source, cleaning and deduplicating the data, and loading it into your destination in a clean, structured format.