Senior Data Platform Manager
Indexed description
Bull is also thousands of engineers, researchers and passionate tech people shaping the future of high-performance computing, AI, and quantum technologies.
Every day, our teams push the boundaries of what is technologically possible – from next-generation HPC architectures to exascale supercomputers – supported by world-class R&D, more than 1,600 patents, and unique end-to-end capabilities spanning hardware design, software engineering, data science and quantum research.
We are a people-centric, innovation-driven company, where collaboration spans Europe, the Americas and India. We share a common vision of a responsible and sustainable innovation that delivers concrete impact for our customers.
Data Engineer Bull Enterprise Data Hub
Contract CDI (Permanent)
Team Data Platform, BL Advanced Computing (HAQ)
Reports to Data Platform Lead
Locations Les Clayes-sous-Bois (Paris) | Angers | Échirolles (Grenoble) | Remote hybrid (up to 3 days/week WFH)
The Role
We are building the Bull Enterprise Data Hub a centralized data platform that consolidates product data across 8+ source systems (SAP, Hotspot, Windchill) into a unified, versioned, API-first platform.
The platform powers
- HPCCAT product catalog for HPC, AI & Quantum
- Executive dashboards GATE program KPIs, S&OP forecast, roadmap views
- Machine-to-machine integrations REST APIs consumed by quoting, digital twin, and external tools
What You'll Do
- Build and maintain ETL/ELT pipelines to ingest data from SAP, HotSpot, vendor feeds, and internal databases
- Design and implement dbt transformation models (staging → intermediate → marts) on PostgreSQL and DuckDB
- Ensure data quality implement tests, monitoring, anomaly detection, and reconciliation with source systems
- Develop and extend the REST API (FastAPI/Python) for data access by downstream applications
- Manage infrastructure Docker Compose, PostgreSQL 16, Alembic migrations, CI/CD
- Collaborate with Product Managers to understand data needs and translate them into reliable data models
- Document data models, lineage, and operational runbooks
Technology
Database
PostgreSQL 16
Analytical Engine
DuckDB (OLAP, columnar)
Transformations
dbt-core + dbt-duckdb + dbt-postgres
Backend API
FastAPI (Python 3.11+)
ORM
SQLAlchemy 2.x
Auth
Keycloak (SSO)
Containers
Docker Compose v2
Migrations
Alembic
Frontend
Streamlit
Version Control
Git / GitHub Enterprise
OS
Linux
What We're Looking For
Must-Have
- 3 to 5+ years experience as Data Engineer, Analytics Engineer, or Backend Engineer with strong data focus
- SQL mastery complex queries, window functions, CTEs, query optimization
- Python proficiency production-quality code, not just scripts
- Experience with relational databases (PostgreSQL preferred)
- ETL/ELT pipeline design batch and/or streaming, error handling, idempotency
- Docker comfortable building and managing containerized applications
- Linux CLI-fluent, can troubleshoot server issues
- Autonomy you'll often be the only person working on a problem. You need to figure things out independently
- dbt experience (any adapter)
- DuckDB or other analytical engines (ClickHouse, Snowflake, BigQuery)
- FastAPI / REST API design
- Alembic / database migration tooling
- SAP data extraction (IDocs, BAPIs, RFC, or file-based exports)
- Keycloak / SSO / PKI implementation
- Experience in industrial / manufacturing / product data environments
- French language (working language of the team and stakeholders)
- High autonomy direct impact on architecture decisions from day 1
- Modern stack open source, no legacy Java/COBOL
- Visible work your pipelines feed executive dashboards and cross-team integrations
- Hybrid flexibility up to 3 days remote per week
- Growth path as the team scales, senior roles and specializations will emerge
- Domain expertise HPC/AI/Quantum is a high-growth market
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