Mohamed Rbaia

1️⃣ 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. 2️⃣ 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. 3️⃣ Led the design and implementation of batch and streaming data pipelines for BlaBlaCar’s SEO train inventory, leveraging reverse ETLs from BigQuery to build 30K+ SEO landing pages for Spanish train operators RENFE and IRYO. 4️⃣ 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. 5️⃣ Built and maintained Datadog alerts and dashboards for live monitoring of both streaming and batch pipelines. 6️⃣ Facilitated the adoption of Scrum principles and practices within two newly established Scrum teams. 7️⃣ Mentored and supported less tenured developers to grow and improve their skill sets. Stack: Google BigQuery · Apache Kafka · GCP · Kubernetes · Airflow · Java · SQL · Data Build Tool (DBT) · Python · Terraform · PostgreSQL · Git · Jenkins · Spring Boot · GCP PubSub · Datadog

1️⃣ Contributed to the implementation of Network Planning and Scheduling algorithms for Southwest Airlines to build a profitable and robust schedule and increase market share. 2️⃣ Built batch pipelines to ingest business metrics and automate the analysis of optimization results, making the team more productive and efficient. Stack: Python · Microsoft Azure · Git · Bash · C# · Bitbucket · Jupyter

1️⃣ 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). 2️⃣ Built batch pipelines to ingest business metrics, automate optimization results analysis and showcase optimization benefits to various stakeholders. 3️⃣ 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. 4️⃣ Built CloudWatch alarms for live monitoring of these critical feeds in production and fast detection of anomalies. 5️⃣ Cleared obstacles and established different methodologies to help a distributed scrum team (3 time-zones) to be effective and self-organized. 6️⃣ Supervised graduation internships focused on airline scheduling problems. 7️⃣ Supported on-site cutover of a critical application for Qantas, replacing a 30+ year legacy system and trained end users before go-live for a smooth transition. Stack: AWS · Couchbase · Java · Python · SQL · S3 · Docker · Git · Bash · CircleCI · Gradle · Datadog · Pubsub · Open API · Jupyter

1️⃣ 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 Stack: Apache Spark · PySpark · Python · Amazon S3 · Amazon Elastic MapReduce (EMR) · Jupyter · CPLEX · Heuristics · Big data