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Description

#Agile Project Management & SAFe Skills

- Scoping and management of Data projects up to production deployment

- Schedule, costing, and budget management.

- Monitoring and reporting of project indicators (progress, prioritization, risk management)

- Facilitating client workshops to gather business needs and use cases for implementation

- Training and awareness for business units on Big Data opportunities and uses

- Agile & SAFe project management with trains of approximately 100 people and multiple SQUADS

- End-to-end Big Data project management: From POC phase to industrialization

- Backlog management, prioritization, facilitation of agile and SAFe ceremonies (PI, ART SYNC, Daily, Sprint Review, Sprint Planning...)

- Writing User Stories using JIRA with acceptance tests

#Big Data Skills

- Implementation of Data Centric, Data Hub & Data Driven architectures with SAFe

- Big Data, Data Warehouse & LakeHouse Architecture with technologies: Hadoop, Couchbase,

Greenplum, S3, KAFKA, Snowflake, ETL/ELT...

- Definition of business objects agnostic of data sources in the Data Hub.

- Implementation of development standards, DevOps & DataOPS pipeline

- Ingestion of multi-source & multi-format data (XML, JSON, CSV...) in batch, micro-batch, streaming via KAFKA, ETL/ELT, API, ESB, CDC...

- Implementation of data ingestion patterns, data quality, interface contracts, rejection recycling policies...

- Data processing in the DataHub via SPARK, ETL/ELT and loading into the DataHub

- Implementation of 24/7 monitoring processes for Big Data application chains

- Hadoop Ecosystem (Hortonworks/Cloudera): HDFS, HIVE, PIG, HBASE, SQOOP, SPARK Python,

- Big Data, Data Warehouse & LakeHouse Architecture with Couchbase technologies

- AWS, GCP & Trusted Cloud S3NS (GCP <=> THALES)

Languages

French
Native or bilingual
English
Fluent

Workplace preferences

Remote only

Primarily works remotely

Freelance
Freelance Big Data Product Owner
May 2021 - Today (5 years and 1 month)
Product Owner within the DATA department of the IT division for the implementation of a Data Centric architecture, Digital Cache Data Hub, and migration to the trusted cloud S3NS: April 2021 to present. Product Owner:
- Work with architects on the study of the Data Centric and Data Driven architecture as part of the IT transformation (4-year vision) to respond to collective tenders.
- Lead the Proof of Concept (POC) for selecting the NOSQL solution to replace the 24/7 POSTGRE Subscriber database.
- Work with the DPO and the CISO team to ensure the solution is RGPD compliant.
- Collaborate with the System Team and Couchbase vendor on the sizing of the PRODUCTION platform and other environments in line with business needs.
- Validate vendor contractual clauses and pricing.
- Populate the Digital Cache backlog and write User Stories in Jira for sprint implementation.
- Define the physical modeling of business objects in the Digital Cache based on the Business Data Model provided by the Data Heritage team.
- Populate Digital Cache data in batch and event-driven (ESB/KAFKA).
- Expose data via APIs (Openshift) in accordance with swaggers.
- Implement performance tests with Néolod, integration tests with ALM (ex QC) and Robotframework.
- Facilitate and participate in various ceremonies (Art Sync, Sprint Review, Sprint Planning, Daily, Retrospective, Backlog Refinement, PI...).
- Lead a cloud POC on AWS to migrate the on-premise architecture to the CLOUD.
- Lead the project for migrating the Digital Cache (Couchbase) to the Sovereign Cloud S3NS.
- Work on API versioning to read multiple backend versions to limit production downtime during the deployment of a new physical model.
ACOSS
Big Data Project Manager
PUBLIC SECTOR
March 2018 - Today (8 years and 3 months)
Paris, France
Integration of the Big Data unit within ACOSS to manage ongoing POCs (Data reliability for DSN 'social security declaration', Debt collection...) and new experiments 'URSSAF fraud detection, AGIRC ARRCO,...). Also, to conduct the study of the target and industrial architecture on several axes:
Project Manager:
- Lead the transverse Big Data core team 'Environment of 10 people'
- Scoping, monitoring, and planning of different use cases.
- Facilitate daily stand-ups and business follow-up meetings
- Integration of new Big Data components such as Spark, Python, NIFI, Oozie..
- Writing an internal document 'Spark for Dummies' to capitalize on and upskill teams on Spark technology.
Architecture:
- Key contributor to the architecture study for positioning Big Data within ACOSS's IT system
- Sharing and feedback on missions within EDF and Banque de France (Organization, Architecture, use cases, RGPD, Production, Processes...)
- Participation in the study of data governance on Big Data and tool selection.
Infrastructure and Target Distribution Choice:
- Development of the target Big Data infrastructure requirements with proper sizing of environments (PROD, Lab, TEST, DEV) to ensure secure, performant, and scalable platforms.
- Writing a detailed comparative document on market distribution choices (Hortonworks, Cloudera, Oracle Appliance) to best guide implementation choices based on ACOSS's needs and challenges.
Industrialization:
- Implementation of the 2019 Big Data roadmap and identification of business use cases for industrialization.
- Gap analysis between the existing (POC) and the target for industrialization on the production platform.
Project Management Big Data Hadoop HBase Spark Hortonworks Cloudera Architecture
Urssaf Caisse nationale
Big Data Project Manager / Architect
February 2018 - April 2021 (3 years and 2 months)
2018: Integration of the Big Data unit within ACOSS to manage ongoing POCs (Data reliability for DSN 'social security declaration', Debt collection...) and new experiments 'URSSAF fraud detection, AGIRC ARRCO,...). 2019/2020: Industrialize BIG DATA work. Manage DSN data feeding into BIG DATA: Feeding & Consolidation Phase. Application Architect. Management:
- Lead the transverse Big Data core team 'Environment of 20 people'
- Scoping, monitoring, and planning of different use cases.
- Facilitate daily stand-ups and business follow-up meetings
- Integration of new Big Data components such as Spark, Python, NIFI, Oozie..
- Writing an internal document 'Spark for Dummies' to capitalize on and upskill teams on Spark technology.
- Implementation of the 2019 Big Data roadmap and identification of business use cases for industrialization.
- Gap analysis between the existing (POC) and the target for industrialization on the production platform.
- Define industrialization patterns such as: application logs, development standards, data governance...
Architecture:
- Key contributor to the architecture study for positioning Big Data within ACOSS's IT system
- Sharing and feedback on missions within EDF and Banque de France (Organization, Architecture, use cases, RGPD, Production, Processes...)
- Participation in the study of data governance on Big Data and tool selection.
Infrastructure and Target Distribution Choice:
- Development of the target Big Data infrastructure requirements with proper sizing of environments (PROD, Lab, TEST, DEV).
- Detailed comparison of market distribution choices (HDP, CDH, Oracle Appliance) to best guide implementation choices based on business needs.