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Bilel TliliBT

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Over Bilel

I build data platforms that scale, govern themselves, and drive real business decisions.

With 10 years of experience across luxury, finance, and beauty — at Christian Dior Couture, L'Oréal, and as Technical Co-founder of Deepera.AI — I've moved from engineering code to engineering strategy. Today, I operate at the intersection of cloud architecture, data governance, and organizational transformation.

At Dior, I didn't just build a data platform. I redesigned its architecture from the ground up — introducing event-driven patterns, a custom execution node orchestrator for parallel GCP processing, end-to-end RLS security models, and a FinOps strategy that cut infrastructure costs by 15–25%. I animated the GCP community, defined the technical roadmap, and presented architecture decisions to senior leadership.

Earlier, I co-founded Deepera.AI after transforming a legacy support company into a product-driven AI startup — building algorithmic trading systems, robo-advisory engines, and NLP banking chatbots deployed as SaaS on GCP and Azure. That experience taught me what it means to own a technical vision entirely, from first line of code to fundraising conversations.

What I bring to a mission:
✦ Architecture that anticipates scale — not just solves today's problem
✦ Governance and security built in, not bolted on
✦ FinOps discipline that makes cloud spending a competitive advantage
✦ A founding mindset — I take ownership, move fast, and think long-term

I work with CAC40 companies, luxury groups, and financial institutions that want a Principal Data Architect who can lead, build, and challenge — not just execute.
  • Frans

    Tweetalig / moedertaal

  • Engels

    Vloeiend

  • Arabisch

    Tweetalig / moedertaal

Kan op locatie werken
Paris (tot 50km)

Werkervaring

  • CHRISTIAN DIOR COUTURE
    Principal Data Architect | GCP
    LUXEGOEDEREN
    juni 2023 - Vandaag (3 jaren)
    Paris, Frankrijk
    Leading the Data System Team (DST) at Christian Dior Couture — owning platform architecture, governance, security & FinOps at enterprise scale. Primary architect for GCP-based data infrastructure.

    🏗️ Architecture & Orchestration
    • Designed event-driven, batch & streaming patterns + DST Task Framework (Cloud Run services & jobs for enrichment, transfer & integration)
    • Built a custom GCP Execution Node Orchestrator — parallel job processing across multiple GCP projects, routing by criticality, execution time & dependencies. Eliminates saturation + ~5% cost saving.
    • Designed the DST Tools Framework — agentic AI platform for Data Engineers & Architects automating: data modeling, lineage, retro-documentation, data quality & backup.
    • Pre-configured GCP project templates (Product, Analytics) with embedded IAM & governance controls.

    ⚙️ DevOps & IaC
    • ~10 Terraform modules: DBT/Dataform deployments, GCP provisioning & cross-project management.
    • CI/CD for data pipelines & infrastructure across all environments.

    🔐 Governance & Security
    • Two-mode data access (direct & indirect via authorized datasets/routines) + RLS combining IAM & BigQuery authorized views for per-user filtering at query time.
    • PAM, WIF (zero-trust), DataGalaxy, automated lineage, RGPD & CI/CD compliance controls.

    💰 FinOps
    • 15–25% GCP cost reduction: AI-driven forecasting, BigQuery on-demand pricing & execution node parallelization. Real-time dashboards via Looker.

    🤝 GCP Community
    • Guilds, guidelines & onboarding programs. Mentored 25+ engineers. Roadmaps to senior leadership.

    ✅ Key Achievements
    → Custom Orchestrator — in prod, smart routing by criticality & dependencies
    → DST Tools Framework — agentic AI for the full data lifecycle
    → Terraform Library — ~10 modules, full IaC & pipeline lifecycle
    → RLS Engine — IAM + BigQuery layer, per-user filtering at query time
    → FinOps — 15–25% GCP cost reduction
    → WIF migration (in progress) — zero-trust identity on GCP
    Google Cloud Platform (GCP) Terraform DBT FinOps Data gouvernance
  • CHRISTIAN DIOR COUTURE
    Technical Lead Data
    LUXEGOEDEREN
    december 2022 - mei 2023 (5 maanden)
    Paris, France
    Stepped into a full leadership role over a team of 25+ Data Engineers at Christian Dior Couture — driving technical standards, platform architecture and security hardening while delivering key data integration and modeling projects across multiple business domains. This role marked the transition from hands-on engineering to owning the technical roadmap and team quality bar.

    🏗️ DBT Architecture — Multi-Team & Multi-Domain
    • Designed a scalable DBT architecture enabling multiple business domains (Supply Chain, Enterprise Performance Management) to work concurrently on the same project — solving isolation, dependency management & deployment conflicts at scale.
    • Defined data modeling standards and layer conventions across domains, ensuring consistency and reusability across business units.
    • Delivered data models for Supply Chain and EPM domains, structuring staging, warehouse and data mart layers.

    🔐 Security & IAM Redesign
    • Redefined IAM roles across all stakeholders enforcing least privilege — reduced attack surface and tightened access boundaries.
    • Introduced custom IAM roles for external contributors scoped to data ingestion & consumption use cases.

    📊 Data Integration — Media & Marketing
    • Designed and delivered Fivetran integration pipelines for Meta, Google Ads, Snap, LinkedIn & Twitter.
    • Built the Media Dashboard — full ingestion via Fivetran + Dataform transformation (3-layer: staging, DWH, data mart) for marketing analytics.

    ⚙️ Platform & DevOps
    • Improved CI/CD processes, redesigned Git flow for multi-team parallel development.
    • Implemented automated retro-documentation and cross-service health checks.

    ✅ Key Achievements
    → DBT multi-team architecture — concurrent domains, no conflicts
    → Least privilege IAM redesign + custom roles for external contributors
    → Media Dashboard — Fivetran to Dataform 3-layer pipeline
    → Automated retro-documentation — continuous catalog accuracy
    Google Cloud Platform (GCP) Fivetran DBT Data gouvernance CI/CD
  • CHRISTIAN DIOR COUTURE
    Data Engineer
    LUXEGOEDEREN
    december 2021 - november 2022 (11 maanden)
    Paris, France
    Data Engineer on the Dior Data Platform — combining design and hands-on development to build scalable ingestion and transformation pipelines across Retail, Sales & Product domains. Contributed to key architectural decisions including the migration to event-driven architecture and the first FinOps & performance optimization foundations.

    🏗️ Architecture & Pipeline Design
    • Proposed & implemented migration from Cloud Function triggers to Eventarc — event-driven architecture improving decoupling, scalability & maintainability. Adopted as platform standard.
    • Designed 4 generic workflow templates (batch, snapshot, messaging, event-driven) — adopted as platform standards across all domains.
    • Introduced containerization patterns and task parallelism to optimize performance & reduce cloud costs.
    • Contributed to architecture of new applications integrated with the Data Platform.

    📦 Data Engineering — Multi-Domain
    • Built end-to-end ingestion & transformation pipelines for Retail & Sales (Xpert, Cegid, Crystal, M3) and Product domains into BigQuery using DBT & GCP services (GCS, Cloud Run, Cloud Workflows).
    • Developed new pipelines via Azure Pipelines, extending platform scalability.
    • Developed and maintained Talend data integration pipelines for multi-source ingestion.

    📊 Monitoring, Observability & Early FinOps
    • Built Looker sanity check dashboards covering quota monitoring, alerting & platform health reporting.
    • Implemented monitoring & alerting framework — proactive detection of processing failures.
    • Laid first FinOps foundations: cost-aware design, task parallelism & performance-first architecture.

    ✅ Key Achievements
    → Eventarc migration — proposed & implemented, modernized platform processing model
    → 4 generic workflow templates — adopted as platform-wide standards
    → Looker sanity check dashboards — quota, alerting & health monitoring
    → First FinOps & parallelism foundations
    Google Cloud Platform (GCP) DBT Terraform CI/CD Python

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Opleidingen

  • Master's Degree in Data Sciences and Machine Learning
    Faculty Of Sciences of Tunis
    2018

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