Mohamed Rbaia - Data Engineer

Paris, France

Experience

Jan 2021 - Present

3 years 6 months

Paris, France

Led the design and implementation of streaming pipelines on GCP and Kafka for BlaBlaCar real-time bus events (delays, cancellations, etc.), ensuring scalable and clean storage in BigQuery to enable efficient analytics and reporting.
Revamped SEO and SEA marketing batch pipelines, leveraging Kubernetes and Airflow to efficiently orchestrate, scale, and manage over 20 million marketing keywords and 250+ interdependent batch workloads.
Built and maintained Datadog alerts and dashboards for live monitoring of both streaming and batch pipelines.
Ensured seamless delivery of these data pipelines by applying software engineering best practices (DRY principle, pair programming, Modular Design, TDD, CI/CD, etc.) and automating data infrastructure and deployments using IaC and Terraform.

Jan 2020 - Dec 2022

3 years

Dallas, United States

Contributed to implementing Network Planning and Scheduling algorithms for Southwest Airlines to build a profitable and robust schedule and increase market share.
Built batch pipelines to ingest business metrics and automate the analysis of optimization results, making the team more productive and efficient.

Jan 2015 - Dec 2020

5 years

Sydney, Australia

Led the design and implementation of disruption management algorithms to optimize Qantas operations, minimize disruption costs, and improve customer experience (3rd best innovation award in AGIFORS Ops 2020).
Built batch pipelines to ingest business metrics, automate optimization results analysis, and showcase optimization benefits to various stakeholders.
Led the design and implementation of streaming pipelines for critical airline feeds (e.g., aircraft maintenance feed (MEL), airline referential data) using Pub/Sub pattern and AWS services like SNS, SQS, and S3.
Built CloudWatch alarms for live monitoring of these critical feeds in production and fast detection of anomalies.

Jan 2014 - Dec 2016

3 years

Nice, France

Performed big data analysis around On-Time Performance (OTP) using diverse airline data sources and provided optimization recommendations powered by our in-house Operations Research algorithms.