Zakaria Hajji

Skills: Data Engineering · Data Architecture · Python (Programming Language) · Data Build Tool (DBT) · Google Cloud Platform (GCP)

Led end-to-end development of a scalable GCP-native Data Platform using DevOps practices (GitHub Actions, Kubernetes), deploying Helm-managed Airflow and dbt pods to orchestrate ETL pipelines and deliver analytics. Designed and implemented a Snowflake- and BigQuery-powered ETL framework to analyze parcel journey funnels, enabling actionable insights for business stakeholders. Tools : Python, dbt core, GCP : GCS, BigQuery, Terraform, Github Actions, Snowflake, AWS ( ECR, EKS), Looker.

- Engineered, built and deployed a scalable Data Platform using Airflow, and Dbt to deliver business insights handling data up to 20TB. - Built and optimised scalable Pyspark ETL Pipelines using AWS Glue to ingest and transform daily app metrics (20GB/5TB) - Built a vector embedding engine for web and atlassian’s confluence service to populate a vector database supporting AI/LLM chatbot use cases - Migrated a hosted Posthog instance ( Clickhouse ) to Posthog Cloud (2 years' worth of events / 400GB) - Upskilling and coaching Tools : Airflow, Dbt Cloud , Gitlab/CI, AWS ( Glue, S3, Athena, Catalog, Schema Registry, RDS), Airbyte, Hightouch, Segment

Integral in the core team developing an ELT platform, consistently interfacing with Amazon Seller API for over 20 brands. - Implemented features on top of GCP data services ( Monitoring, Partitioning and Migration frameworks) - Participated in data architecture strategies and roadmap ( scaling data lake and datawarehouse on GCP) - Benchmarked data visualisation tools and liaised with GCP Accounts for Looker pre-implementation

Google Cloud Professional Data Engineer certification. Contributed in several projects: Migration of Data Ecosystems from Hortonworks Hadoop HDP to Google Cloud Platform (GCP) - Developed and optimized agile (CI/CD) data pipelines using PySpark, ensuring adherence to best practices on GCP. - Applied PySpark optimizations for improved data processing performance, ensuring a robust and scalable data platform. Insurance Covid Support Chatbot with Google's Dialogflow. - Oversaw the project from initial concept to final execution, created advanced dashboards to track user engagement and metrics. Predicting customer churn for a Fitness group - Improved client retention through data-driven insights and Machine Learning.

Co-founded a B2B marketplace for land freight and FMCG firms: Embedded tracking, data aggregation and serving on GCP

Using Deep learning for anomaly detection based on system logs. - Research and review of state of the art ML/ DL approaches and papers for Anomaly Detection. ( PCA, K-means, TSNE.) - Implementing a PoC Architecture using LSTM architecture for root cause anomaly detection (pandas, sklearn, tensorflow, onnx, Cloud GPU training environments ) - Animation of Embedded AI Training sessions, Participation in Strategic Innovation Workshops

- Digital transformation of an industrial unit using Siemens's Mindsphere IoT System Solution (Open Cloud IOT OS) deployed on Azure. - Study of the industrial communication infrastructure and the Manufacturing Execution System - Development and integration of an IOT application prototype for Predictive Maintenance Tools : (SQL | Node-Red,Kafka, Mongodb, MQTT/websocket, Map reduce, Spark, Cloudfoundry).

- On-field business analysis of requirements and business needs, study of industrial communication protocols. - Implementation of a portable Monitoring Platform for Maintenance KPIs. Tools : .Net/ C#, Azure IOT Hub