Data Engineer
Confirmed on the employer's own hiring board on Oct 7, 2026. First seen by Alion on Sep 27, 2026.
Join our established Data Team as a Data Engineer. In this hands-on engineering role, you will build and run data pipelines and infrastructure, integrating various systems into Databricks. You will have real ownership of the entire process, from stakeholder conversations to design, infrastructure provisioning, and orchestration. You will also have the opportunity to integrate new systems into the Data Platform. Key responsibilities include building and maintaining ETL data pipelines, defining infrastructure as code, building and integrating APIs, containerizing workloads, and owning the operational side of what you build.
Missions
- Construire et maintenir des pipelines de données ETL en Python, orchestrés avec Airflow, en traitant des données dans Databricks sur Azure.
- Définir l'infrastructure en tant que code avec Terraform, et l'expédier via des pipelines Azure DevOps avec des bibliothèques partagées publiées en tant qu'Artéfacts.
- Travailler directement avec les ingénieurs analytiques et les analystes de données pour recueillir les exigences, examiner les options et traduire ce qu'ils demandent en ce dont ils ont besoin.
Profil recherché
- Terraform, or experience with an alternate infrastructure as code tool and a willingness to learn- An understanding of how to tackle different extraction sources, such as databases, service, API endpoints, etc
- Strong Python skills, with the habits that make code maintainable: tests, structure, review
- Familiarity with DBT best practices and implementation
- Working experience with Airflow or a comparable orchestrator
- Databricks (incl. Asset Bundle deployment) or similar data platform tool experience
- Experience on Azure, and with Azure DevOps for CI/CD (Pipelines, and Artifacts for shared packages)
- Enough networking to be useful. DNS, TLS, firewall rules, private endpoints, VNets. You don't need to be a network engineer, but "it's a networking problem" shouldn't be where you stop
- API design and integration (e.g. FastAPI)
- Real comfort in the terminal: git, shell, debugging a process on a box/container you've SSH'd into, without reaching for a GUI
- Docker, and comfort with how containers behave in production vs development
- You communicate comfortably in English, in writing, with colleagues across several countries
- You can design a system and explain it: a clear architecture diagram and design document that a mixed audience of engineers and non-engineers can both follow
- You design in the open. You write proposals, you invite review early, and you change your mind when someone makes a better argument
- You can sit with a stakeholder who doesn't know what they want yet and leave the room with a specification. Running a workshop shouldn't scare you
- Experience in a multi-brand, multi-country or post-merger environment, where the same concept is modelled three different ways and someone has to reconcile it
- Data modelling for analytics (Medallion architecture, dimensional modelling)
- Streaming or event-driven work (Kafka, Event Hubs)
- Data governance, lineage or cataloguing tooling