> Markdown version of [/jobs/ext/725657-senior-data-platform-manager](https://www.wearedevelopers.com/jobs/ext/725657-senior-data-platform-manager). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Platform Manager - **Company:** Atos - **Location:** Tours, France (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, BigQuery, Continuous Integration, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Security, Relational Databases, Database Queries, Linux, Document-Oriented Databases, Executive Information Systems, IDoc, Python (Programming Language), PostgreSQL, Online Analytical Processing, Public Key Infrastructure, Query Optimization, SAP (Applications), SAP NetWeaver Data Management, SQL Databases, SQLAlchemy, Data Streaming, Windchill, Enterprise Data Management, Okta, Data Ingestion, Snowflake, Backend, Git, Fastapi, Database Migration, Containerization, Github Enterprise, Production Code, Front End Software Development, Vertica, Api Design, Restful APIs, Streamlit Framework, Data Pipelines, Docker, Web Api - **Published:** June 29, 2026 - **Apply:** https://fr.indeed.com/viewjob?jk=edd9e823240731a0 ## About the Role Do you have experience in SQL?, 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 Nice-to-Have * 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) ## Description 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 You will join a small, high-impact team (3 people) and own the data engineering layer: ingestion pipelines, transformation models, data quality, and warehouse infrastructure. 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 ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Stop Committing Your Secrets - GIt Hooks To The Rescue!](https://www.wearedevelopers.com/videos/573-stop-committing-your-secrets-git-hooks-to-the-rescue) ## Related Articles - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Find a Developer Job: 12 Best Job Sites For Developers](https://www.wearedevelopers.com/magazine/165-find-a-developer-job-12-best-job-sites-for-developers) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)