Nabil - Chef de projet SQL SERVER

Ref : 111122F002

Profil

Chef de projet, Formateur, Architecte (63 ans)
Domicile

94500 CHAMPIGNY/MARNE
Mobilité

Ile-de-France
Tarif Journalier Moyen
Voir le tarif

Compétences

Unix

SQL Server

Oracle

Unix AIX

Unix Solaris

VMware

Windows Server 2003

Windows Server 2008

Expériences professionnelles

Role: Databricks Expert

Teamwork
novembre 2024 - janvier 2025
Achievements:
• Data & AI Platform Architecture review for customers.
• Help & Upskilling of Teamwork Data team.
Technical Environment: Azure Databricks
Role: AI Expert

Freelance Geode
août 2024 - aujourd'hui
Achievements:
• Architecting, Developing and deploying an GenAI Stack to make responses for RFPs
(Request for Proposals).
Technical Environment: Kubernetes, Ollama, Milvus, Llama3, Langchain, Postgres, PyMuPDF4LLM
Role: Entreprise Architect (Cloud & Data) and Databricks Lakehouse Expert

Plastic Omnium
mars 2023 - juillet 2024
Achievements:
• Databricks Lakehouse design & deployment with Data Mesh architecture (Spoke and
Hub)
• Artificial Intelligence Architecture (Machine Learning, Deep Learning & Generative AI):
from Development to Production using MLOps and LLMOps.
• Migration from Cloudera Hadoop to Azure Databricks Lakehouse
• Project coordinator: Dada Catalog, Data Governance (Semarchy, Custom Data
Governance Tool - Lineage, Security, Modeling), Data Marketplace and Data
Lakehouse
• Enterprise Architecture: Archi (Archimate), Data & Cloud principals, Business
Architecture (capabilities), Data Architecture (Analytic modeling, Transformation &
Visualization), Infrastructure (Components Architecture, security models, Databricks
Lake House Infrastructure)
• Azure CI/CD pipelines Applications & Azure and Databricks deployment infrastructure
(Terraform)
• Azure & DataBricks FinOps Monitoring.
• DataBricks performance optimisation.
• Cloudera maintenance
Technical Environment: Azure: Databricks, Azure Data Lake Storage, EvenHub, IoTHub, EventGrid, AKS, ACA, Semarchy, AD SCIM provisioning, Network Peering, Private DNS zone, Firewall rules
Role: Azure Databricks Expert

Oddo
novembre 2022 - juin 2023
Achievements:
• Migration of Data Science project from Anaconda to Azure Databricks: Financial Time
Series Model Prediction (300 Models)
• Deployment and designing of MLops process
Technical Environment: Azure: Databricks, Azure Data Lake Storage, Anaconda, Pandas, Scikit Learn
Role: Big Data/Spark Expert and Solution Architect

Intermarche
avril 2021 - février 2023
Achievements:
• Azure Databricks pipelines Optimization, architecture Review, Best Practices
• Azure Data Hub Architecture improvement adding the usage of Delta Lake (ADLS
Gen2), Metadata management and the Document Architecture process.
• Data quality improvement with Data Profiling, Data Validation and Data Observability
(Deequ: Spark Library)
• CI/CD pipeline review and development of Best Practices.
• Improvement proposition about quality metrics, data governance, Cloud Resource
cost reduction, resource monitoring, architecture patterns, infrastructure templates.
• Data sharing solution: design and implementation.
• Data Lake management: backup strategy, environment refresh.
• Design and Development of a Data Quality Tool (Spark, Scala, IntelliJ idea)
• Databricks Runtime Migration from 6.x to 7.3 LTS / 7.3 LTS to 10.4 LTS
• FinOps: Setup of Best practices to reduce cloud costs (decrease from 300K€/Month to
200K€/Month
• Design/Development and Implementation of a Databricks pipeline for monitoring and
explicability of consumptions and costs of cloud resources (Spark, SQL, Python, Delta
Live Table, Databricks SQL, Power BI)
• Development and upgrade of new rules in an Anomaly Detection System based on
business rules for stores treatment of special offers (Databricks Spark, Python)
• Synapse vs Databricks vs Snowflake vs BigQuery comparatives for usage of a
Lakehouse.
• Study of impacts for shifting from Azure Databricks hive Metastore to Databricks Unity
Catalog.
• Proof of Concept for multi-cloud (AWS, Azure) Data Plaform and Data solutions.
Technical Environment: Azure: Databricks/Spark, Data Factory, SQL Database, Data Lake, Blob Storage, EvenHub
Role: Auditor

EDF
décembre 2020 - février 2021
Achievements:
• Audit of an Elasticsearch application (version 6.8, 400Tb of data, Cluster composed of
105 Nodes)
• Domain of Observability (Index Lifecycle Management), Streams of technical &
application logs and measures.
• Revue of Java & Python code (DevSecOps best practices)
• Revue of Elasticsearch Data Model (Static/Dynamic schemas, usage of Analyzers,
Indices usage, Fields normalization and naming, ECS compatibility, Continuous
Aggregation …)
Technical Environment: Elastic Stack, Java/Python, Jenkins
Role: Big Data/Spark Expert

Banque de France
août 2017 - mars 2021
Achievements:
• Hortonworks platforms administration (HDP 2.x - 3.1, HDF 2.x - 3.x): Installation,
clusters configuration, security configuration (kerberization, data encryption), service
management, designing and configuring queues, HDFS and Yarn sizing, configuring
Knox and Ranger, clusters monitoring
• Defining the best practices for Hive (partitions, bucketing, ACID and LLAP) and for
Spark.
• LLAP configuration and resources allocation
• Architecting the ingestion strategy (batch & near real-time process, Change Data
Capture, Streaming, Triggers)
• Architecting a pricing assets application on an open source and distributed
environment
• Installation of a Spark Cluster on Kubernetes
• Designing and Deploying Elasticsearch indices and analyzers for an internal
application
• Testing and validating the usage of sqoop for data ingestion from Relational Database
Management Systems (Oracle, Postgres, MS SqlServer) to the DataLake within
Secure and Authenticate Connections.
• Kafka qualification for data streaming and real-time data analysis.
• Audit, qualification and designing Big Data development environment and integration
with Hortonworks Data Platform (Hadoop) for a Data Lake use case (Pig, Sqoop,
Hive, Spark, HBase, Elasticsearch,…)
• Spark pipelines analysis, optimization, performance improvement and data
anonymization (Java, spark, Hortonworks)
• Designing Kubernetes Patterns for database systems, logging systems and
monitoring systems (Postgres, Barman, Filebeat, Elasticsearch, Logstash, Kibana,
Fluentd, Prometheus, Grafana etc., Kafka, Pulsar)
• Auditing many Big Data applications and Pipelines (Sqoop, Hive, Spark,
Elasticsearch, HBase, Tez)
• Optimizing many Spark, Hive/Tez applications/Pipelines in Java and Python
• Defining Python best practices
• Proposal about Big Data Ingestion strategy
• Designing the Data lake, data type zones (Silver, Bronze, Gold and Sensitive), Data
Catalog and Lineage.
• Adding a new functionality to AWS Deequ (Data validation Development in Spark and
Scala)
• Customization of Spark (SDL & VTL parser) for ECB Anacredit application.
• Migration Affects from HDP 2.6.3 to CDP-Cloudera Runtime 7.2.6: What projects have
to change (HiveQL, Spark, etc.)
• Audit Java code and Elasticsearch Data model (ILM, logs and Metrics)
Technical Environment: Hortonworks HDP, Hive/LLAP, Tez, Spark, Sqoop, Kafka, Java, Python, Kubernetes, OpenShift, Zeppelin, Jenkins
Role: Managing a Big Data and Data Science training team

Next Challenge
2016 - 2017
Achievements:
• Designing a training program in Big Data domains
• Advising and Helping customers for choosing and setting Big Data Architectures
(Lambda, Kappa, Zeta, SMACK, DataLake)
Technical Environment: Cloudera CDH, Kafka, Pulsar, Cassandra, MongoDB, Scala, Python
Role: Product Owner for BigData As A Service

Orange-CloudWatt
2016 - aujourd'hui
Achievements:
• Setting up many Hadoop production environments (Cloudera, Hortonworks, MapR)
• Managing requirements
• Management of schedule and defining priorities
• Benchmarking Hadoop Distributions (Cloudera, Hortonworks, MapR)
• Defining recommendations for customers using Orange Cloud Platforms
• Setting the pre-configured versions with optimized operating system and Hadoop
parameters
• Developing the Cloud distributed image factory process
• Designing technical architecture for huge volume cluster
• Architecting some data science use cases for customers: Crawling social networks,
storing data in Hadoop Distributed File system, processing fixed image with spark and
tagging them automatically, Inserting the produced tags in elastic search feeding an
oriented graphics internet browser.
Technical Environment: OpenStack
Role: Big Data Architect

Umanis
2015 - 2016
Achievements:
• Designing a big data architecture (lambda architecture) for data integration including
Hadoop cluster, SAP Hana Cluster and Talend Data Integration
• Development of a near real time analytical dashboard with Seller performance
graphics and objectives alignment
• Design of a system to predict incomes in the future using spark machine learning to
access historical data and others environmental data like weather and holidays
• Crawling many internet sources about Arab world political, social and cultural blogs
and newspaper in arabic, french or english. Storing the data on a Hadoop cluster and
indexing them with Elasticsearch. Improving the search function of Elasticsearch by
generating dynamic multilingual thesauri based on the Deeplearning model
Technical Environment: Cloudera CDH, SAP Hana, Elasticsearch

Études et formations

Databricks training: Certificate of Completion of Apache Spark Tuning & Best Practices

2019
Certificate in Deep Learning,

Coursera
2018
Togaf 9 Level 1 & 2 Certificate,

the Open group
2015
PhD in Computer Science

PhD, Paris 11
1988
Master in Electronics and Computer Science

Master, Paris 11
1987

Langues

Anglais - C2

Autres compétences

ABOUT ME
- About 40 Years of professional experience in IT
- Expert in Advanced Data Analytics on Cloud and On Premise
- Databricks & Snowflake Partner
- Mastering Data Cloud Architecture and Lakehouse Solutions
- Experience in architecting, designing and deployment of Data platform
- Governance and Data project management
- Databricks Lakehouse Expert (5 certifications, 6 Accreditations)
- Research in Natural Processing Language and Information Retrieval.
- Speaker in International conferences:
* Salon Big Data in Paris - March 2016,
* Data Science & Big Data Analytics in Toronto – Mai 2018,
* Journée Big Data Mining et Visualisation Paris 8 – Juin 2018,
* IHEC Carthage summer school July 2018,
* International Conference on Computer Science & Cloud Computing in Barcelona - July
2018,
* Data Science & Big Data Analytics in Tokyo - March 2018
* Advances in Cloud Computing, Data Mining, Data Science & Big Data Analytics in
Tokyo (Japan) – March 2019.
* Advances in Cloud Computing, Data Science & Big Data Analytics in Toronto (Canada)
May 2019.
* Sitic Africa: Panel: Artificial Intelligence & Big Data usage in banks, June 2019
SKILLS
Data Science • Natural Language Processing (NLTK, GenSim, spaCy, sparkNLP, GenAI)
• Deep Learning (TensorFlow, Theano, Keras)
• Machine Learning (SparkML, Sklearn, mlflow)
2
• Generative AI (transformers, llama3.x, llama Index, langchain …)
Big Data • Hadoop Ecosystem (Cloudera, Hortonworks)
• NoSQL Data Stores (MongoDB, Cassandra)
• Elastic (Search, Logstash, Kibana)
• Data Streaming (Kafka, Pulsar and Spark)
• Databricks / Snowflake
Data Management • Data Quality (Talend, AWS Deequ, DataBricks, SnowFlake)
• Data Lineage (DataBricks, SnowFlake)
• Data Integration (Talend, Azure Data Factory)
• Data Governance (DataBricks, DataGalaxy, Semarchy, Alation, SnowFlake))
IT Governance
• Enterprise Architecture (Togaf)
• Cobit
• Project Management (PMI, Agile - SCRUM)
• Data Analysis
IT System & Cloud Administration • Database Administration
Oracle, MS SQL Server, MySQL, SAP Hana
• Operating System Administration
Windows server, Linux Centos
• Big Data Environment
Hadoop (Cloudera, Hortonworks)-HDFS-YARN, Spark (Core, SQL, Streaming, ML,
GraphX, Scala, Python), MapReduce (Hive, Pig), Flume, Kafka, MongoDB, Container
(Docker, cgroups), Mesos, Kubernetes, OpenShift, Databricks
• Programming Languages
C++, Java, Python, Scala
• Cloud
Openstack, Kubernetes, AWS, OpenShift, Azure

AWARDS AND CERTIFICATE
§ Databricks training: Certificate of Completion of Apache Spark Tuning & Best Practices, June 2019
§ Certificate in Deep Learning, Coursera, 2018
§ Togaf 9 Level 1 & 2 Certificate, the Open group, 2015
§ Zachman Certified, 2014
§ MongoDB Certified Developer Associate, 2014
§ CISM (Certified Information Security Manager), ISACA – 2011
§ CobiT Foundation Certificate, ISACA - 2011
§ CISA (Certified Information System Auditor), ISACA – 2010
§ OCA (Oracle Certified Associate), Oracle – 2003
LANGUAGE
English, French and Arabic

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Nabil - Chef de projet SQL SERVER

Chef de projet, Formateur, Architecte (63 ans)

94500 CHAMPIGNY/MARNE

Role: Databricks Expert

Role: AI Expert

Role: Entreprise Architect (Cloud & Data) and Databricks Lakehouse Expert

Role: Azure Databricks Expert

Role: Big Data/Spark Expert and Solution Architect

Role: Auditor

Role: Big Data/Spark Expert

Role: Managing a Big Data and Data Science training team

Role: Product Owner for BigData As A Service

Role: Big Data Architect

Databricks training: Certificate of Completion of Apache Spark Tuning & Best Practices

Certificate in Deep Learning,

Togaf 9 Level 1 & 2 Certificate,

PhD in Computer Science

Master in Electronics and Computer Science

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