Mohamed Ali

+ Rebuilt the data infrastructure end-to-end, including architecture design and implementa

tion of core data engineering components.

+ Optimized DBT Modeling layer by implementing an incremental approach to process ing, storage and updates which lead to decrease in cost by 30% and decrease in processing time by 70%, additionally migrated from DBT local to DBT Cloud with zero downtime.

+ Configured GCP Datastreams to connect AWS Aurora databases to BigQuery for

real-time data syncing.

+ Established a staging environment, resulting in a 80% increase in feature development efficiency.

+ Implemented a real-time GA4 event pipeline: data ingested via Pub/Sub, pro cessed and enriched in Databricks, and written to BigQuery for low-latency analytics.

+ Designed and implemented data pipelines using Apache Airflow and Python to integrate HubSpot data (forms, contacts, deals and Sales Leads) into the company's reporting

infrastructure.

+ Built automated tests using Pytest and deployed them in Google Cloud Run, trig

gered by PRs in GitHub via GitHub Actions.

+ Hired and built a small data team (Data Scientist, Junior Data Engineer) to scale

and manage the company's growing data needs.

+ Tech Stack: Python, SQL, DBT, Airflow, BigQuery, Databricks, GA4, Pub/Sub, Cloud Composer, Cloud Run, GitHub Actions and PyTest

+ Designed the data architecture for the Competitor Intelligence department to collect

and structure market and project data.

+ Developed web crawlers to gather information on open positions within Cintellic's

customer base.

+ Planned and executed migration of internal on-premise infrastructure to Microsoft Azure.

+ Built internal reporting solutions using Power BI to provide actionable insights for

stakeholders.

+ Tech Stack: Python, SQL, Azure Synapse,Azure Data Factory, Power BI, Web Scraping,Zyte API

+ Built the entire data infrastructure from scratch, including architecture design and implementation of core data pipelines in Apache Airflow and DBT Cloud models.

+ Created DBT transformation models and developed advanced customer metric aggrega tions.

+ Configured AWS Data Migration Service (DMS) to replicate data in real-time from Aurora MySQL to AWS Redshift, ensuring up-to-date analytics while orches

trating downstream DBT transformations.

+ Built dashboards in Metabase for management and shareholders, providing visibility into

company performance and operational KPIs.

+ Developed a customer classification algorithm to segment shareholders into buckets,

enabling more targeted approaches for client reactivation.

+ Created an event-driven data exchange pipeline between the company and stake holders using AWS EventBridge, S3, and Lambda functions.

+ Created metrics dashboards in Metabase for product and sales teams, supporting moni toring of customer growth and business performance.

+ Tech Stack: Python, SQL, DBT, Airflow, AWS DMS, AWS Redshift, AWS S3, AWS Lambda, AWS EventBridge