OMAR LARAQUI
FREN
GitHub
← HOME

CLIENTS, ROLES AND ENGAGEMENTS

Professional experience.

Real projects and responsibilities, from Data engineering implementation to architecture and technical leadership. Forward Deployed Engineering is my career direction, not my current title.

DATA & AI TECH LEAD7 CLIENTS / COMPANIES8 ROLE PERIODS

Work and responsibilities

From engineering delivery to technical leadership

01Colombes, France

ENGIE

Data Tech Lead

  • Migration from Palantir Foundry to an AWS and Databricks Lakehouse architecture.
  • PySpark data pipelines and Bronze / Silver / Gold layers on Delta Lake.
  • DataOps practices for deployments, pipeline monitoring, Spark performance and FinOps.
  • Reliable, governed datasets supporting Data Science and generative AI use cases.
AWSDatabricksPySparkDelta LakeDataOpsFinOps
02Puteaux, France

Groupe Alain Afflelou

Data Architect & Tech Lead

  • Cloud solution architecture and delivery of robust ingestion and transformation pipelines.
  • APIs and system integrations using Azure Functions and Azure API Management.
  • Security, GDPR-aware governance, cost optimization and operational performance.
  • Technical workshops with data science, stewardship and analytics stakeholders; code-review practices.
AzureDatabricksAzure FunctionsAPI ManagementFinOpsGovernance
03Paris, France

iQera

Senior Cloud Data Engineer

  • Migration of BI cubes, fact and dimension tables from multiple sources to Azure Data Lake.
  • Python, SQL and PySpark ingestion and transformation using Delta and Parquet.
  • Bronze / Silver / Gold layers, access controls and Azure DevOps deployment pipelines.
AzureDatabricksPySparkData FactoryAzure DevOps
04Paris, France

AXA

Data Tech Lead

  • Engaged business departments to understand data requirements.
  • Improved computational performance and data-processing code quality.
  • Monitored pipelines for operational reliability and output data quality.
Data leadershipSparkQualityStakeholder collaboration
05Paris, France

AXA

Cloud Data Engineer

  • Migrated SSAS tables from SQL Server to Azure Data Lake.
  • Built analytics flows with Scala, Python, SQL and Spark 3 using Delta / Parquet.
  • Automated Azure Data Factory pipelines and Azure DevOps releases.
  • Implemented data-quality checks with Deequ and BDD/Cucumber Spark testing.
Azure Data FactoryDatabricksScalaPySparkDeequCucumber
06Paris, France

Natixis

Hadoop Data Engineer

  • Prototyped and engineered a Hadoop architecture for market reserve calculations.
  • Python, PySpark, Scala and Hive SQL processing, scheduled with Control-M.
  • BDD tests with Cucumber/Gherkin and CI/CD using Jenkins, XLDeploy and XLRelease.
HadoopSparkScalaHiveControl-MJenkins
07Puteaux, France

Ingeniance

Data Engineer / Scientist — internship

  • Research and prototype for CV parsing, layout segmentation, classification and named-entity recognition.
  • Stacked classification with Naive Bayes, SVM and Random Forest; résumé reports 89% precision.
  • Integrated the approach with a company portal supporting candidate ranking and matching.
PythonNLPNERScikit-learnClassification
08Levallois-Perret, France

Edifixio

Data Engineer / Scientist — internship

  • Integrated an Angular / Node.js application with Salesforce REST APIs.
  • Explored NLP and deep learning with Python, spaCy, Word2Vec and Seq2Seq.
  • Contributed to Salesforce integrations, permissions, workflows and REST tests.
SalesforceREST APIsAngularNode.jsPythonNLP

EDUCATION

ENSIMAG2019–2020

Research Master’s degree in Artificial Intelligence and Semantic Web

ENSIMAG2018–2019

Engineering degree in Information Systems Engineering

ENSIAS2016–2018

Engineering degree in E-Management and Business Intelligence

CERTIFICATIONS

  • Databricks Certified Data Engineer Professional
  • Databricks Certified Data Engineer Associate
  • Azure Databricks Platform Architect
  • Databricks Certified Associate Developer for Apache Spark
  • Microsoft Azure Data Engineer Associate (DP-203)
  • Astronomer DAG Authoring for Apache Airflow 3
  • Microsoft Azure Data Fundamentals (DP-900)
  • Microsoft Azure Fundamentals (AZ-900)

Summaries based on the provided résumé. Responsibilities were rewritten without inventing numerical outcomes.

FROM EXPERIENCE TO PROJECTS

Experience shapes the projects.

Explore projects ↗