Mohamed E.

Proof-of-Concept aimed at migrating and evaluating a Big Data ecosystem (Hadoop/HDFS/Spark/Hive) to Google Cloud Platform. Objectives: validate technical feasibility, measure performance and costs (TCO) by comparing the existing architecture (Exadata + Indexima) with a GCP solution (BigQuery, Dataproc/Dataflow), and define the operational trajectory (target architecture, security, costs, run).

Responsibilities:

- Comprehensive audit of the existing Hadoop environment (topology, Spark/Hive jobs, ETL patterns, storage, catalogs, security) and mapping of application dependencies and data flows.

- Design of the target GCP architecture (ingest → storage → processing → analysis): GCS, Dataproc / Dataflow / BigQuery, data transfer (Storage Transfer / gsutil / Sqoop alternatives), cataloging (Data Catalog / Hive metastore), and Airflow pipelines.

- Implementation of a comparative benchmark protocol between Exadata+Indexima and BigQuery: representative datasets, analytical and ETL workloads, concurrency scenarios, and cost metrics (queries, storage, slots).

- Optimization of schemas and formats (Parquet/ORC), partitioning/clustering, materialized views, and BigQuery optimization strategies (slot reservations, uncorrelated columns) to replicate real loads and maximize comparability.

- Security & governance: CMEK (customer-managed encryption keys) recommendations, fine-grained IAM, VPC Service Controls, data lineage, masking, and GDPR compliance.

- FinOps & sizing: TCO estimation, cost analysis per query, recommendations for BigQuery / Dataproc slot sizing, and cost optimization strategy (storage classes, partition pruning, reservation autoscaling).

- Execution of load tests, performance tuning, implementation of monitoring (Stackdriver / Cloud Monitoring, BigQuery audit logs), and run & incident playbooks.

CERTINERGY – ENGIE: Prométée Project – Global redesign of the IT system around energy savings management and production (CEE), with the objective of modernization, IT system urbanization, and compliance with data, security, and scalability challenges.

- Mission:

+ Conduct a complete audit of the existing system (application mapping, business processes, data flows).

+ Design of the target architecture oriented towards cloud, microservices, and API-first.

+ Introduction of strategic technical components:

+ + Middleware (API Management, EDA, cache),

+ + Centralized IAM with SSO.

+ + BPM.

+ + BI, OPS, and automation.

+ Integration of an Event-Driven Architecture (EDA) for business processes.

+ Data governance: MDM strategy, traceability, security (encryption, key rotation).

+ Steering the transition to an AWS cloud platform, within a secure and scalable framework.

+ Collaboration with business and technical teams to ensure strategic alignment.

- Deliverable: Reporting documentation including reports, HLD and LLD documentation, Terraform source code, Node.js source code (TypeScript), Golang, Python, and Java (Apache Beam, Cloud Dataflow), Airflow source code.

Technical Stack: AWS Cloud, Apache Airflow, Apache Nifi, Apache Beam, AWS IAM, AWS Cognito, AWS Cedar, Keycloak, OPA, AWS SQS, Kafka, MS Azure, MS Azure AD, TypeScript, PHP, Golang, Python, OAuth2, Unix, Linux Debian, Sonar, Open Metadata, Grafana, Prometheus, ELK, Postgres, Helm, Kubernetes, Jenkins, GitLabCI, Camunda, Flowable, Kong, KrakenD, Axway, Camunda, Flowable, Archimate, Togaf, UML, Security By Design, Zero Trust.

Took over the "LOSS PREVENTION" Fraud Prevention project, decommissioning BOKS & PosLog.

Mission:

Inventory and assessment of the existing system.

Establishment of supports for the Move To Cloud.

Conducting workshops and solution architecture work: functional, technical, API, data, and cloud.

Technical scoping, technical documentation, costing, and estimation for new features, establishment of the roadmap. Definition of the technical foundation.

Implementation of the Move To Cloud strategy to ensure the migration of the existing system to the new cloud foundation.

Architecture and implementation work for the network topology on the new Landing Zone.

Implementation of the cloud foundation for a Landing Zone on GCP.

Implementation of an infrastructure and data security policy, as well as vulnerability tests (with Pentesting).

Establishment of a mesh for hybrid connectivity (On Prem OVH & ARI Data center & GCP).

Contribution to infrastructure implementation, data and application development tasks, DevOps and SecOps tasks.

Implementation of monitoring and alerting policies for: Google Cloud Logging (Sink), Google Native Dashboard, BigQuery, Cloud Storage, Grafana, Datadog, quotas.

Implementation of a backup and restore strategy.

Implementation of a strategy to ensure high availability and high performance.

Management of L3 incidents, establishment of continuous improvement plans via post-mortems (blame-free), implementation of a chaos engineering strategy (tests) to ensure infrastructure resilience and robustness, as well as the establishment of disaster plans.

Support for teams and creation of documentation.

Deliverable: Reporting documentation including HLDs, LLDs, and PADs, then Terraform source code, Nest.js and Python source code.