BWI — which stands for Blue Water Intelligence, was established in June 2022 in Toulouse, France. BWI clients like to see us as their basin digitization company. BWI specializes in the monitoring of inland surface water reserves around the globe. BWI brings together in-situ data, spaceborne observations and machine learning to feed and empower hydrological and hydrodynamical models, and provide clients with data and insights on their points of interest. A provider of online subscription-based services, BWI aims to make scalable — across space and time — hydrological forecasts to address climate change induced water stress. Improvements in the prediction of water availability, water quality, floods, and droughts at local and regional scales will help the population and businesses build climate resilience, as well as enable scientists to understand the water cycle deeper.
— Terraform IaC for dev/stage/prod (modules, remote state, reviewable plans).
— Operate Kubernetes (managed cloud K8s): cluster lifecycle, upgrades, autoscaling, scheduling, Operators/CRDs. — CI/CD & GitOps: Bitbucket (Cloud) + Bitbucket Pipelines → GitOps deployments using Helm (Argo CD or Flux compatible Helm charts).
— Docker/OCI: secure, minimal images, multi-stage builds, image scanning. — Observability & SLOs: Prometheus, Grafana, OpenTelemetry, Loki, alerting.
— Security: IAM, mTLS/service auth, secrets management (Vault/Kubernetes secrets sealed), vulnerability scanning, network policies. — Data pipeline ops: batch/stream (Spark, Dask, Prefect or Airflow), large-file transfers to S3‑compatible storage, checkpointing and retry patterns.
— Cost optimization: rightsizing, spot/preemptible strategy, storage lifecycle. — Runbooks, on‑call, incident response and documentation.
— Managing heterogeneous company workstations (Linux, Windows, Apple,…) from the craddle to the crave, all along their lifecycle.
— Production Kubernetes operations (managed cloud).
— Terraform with modular patterns and remote backends.
— Bitbucket Cloud + Bitbucket Pipelines experience; Helm-based deployments.
— Docker/OCI image best practices and image scanning workflows.
— Observability stack: Prometheus/Grafana/OpenTelemetry.
— Python for automation; Bash for ops.
— S3-compatible object storage experience; familiarity with Scaleway advantageous.
Nice-to-have tools | knowledge | skills:
— GDAL, xarray, satellite/altimetry pipeline experience, pyarrow.
— tensorflow serving | 1password | fastapi | uvicorn.
— Self-hosting LLM + opencode integration.
— Python OOP skills a huge plus.
— On-site Toulouse, ideally, or Paris.
Equal Opportunity Statement:
We are committed to diversity and inclusivity.