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We’re looking for a Hydrologist to join our team. As our in-house Hydrologist, you’ll play a critical scientific and strategic role within a multidisciplinary team. You will be responsible for analysing and interpreting hydrological data, stressing hydrological models at our clients, supporting the integration of hydrological knowhow into our software and client solutions at pre-sales, project and operational stages. You’ll bridge the gap between Earth observation, data science, ground instrumentation, and public/private water management clients and partners.

Core responsibilities

• Conduct inventories and analyses of surface water, groundwater and snowpack dynamics using remote sensing, in situ data, and historical records. 
• At pre-sales stage, support business development and institutional engagement activities as a domain expert.
• At implementation stage, manage model training phase, interact proactively with clients.
• At operational stage, contribute as expert to forecast performance accountability and improvement of client satisfaction through the bettering of models and accuracy.
• Foster BWI data integration into client information systems by showcasing use cases and value.
• Design and write functional specifications for internal and client-facing software tools. 
• Collaborate with engineers, and sales teams to align hydrological insights with user needs. 
• Train internal teams (software/sales) and external users (workshops) on key hydrology concepts. 
• Prepare engaging, scalable hydrology training materials. 
• Manage water quantity/ quality instrumentation projects, including calibration and validation campaigns. 
• Interpret meteorological, hydrologic, and snow data to support ongoing projects. 
• Train hydrological models to predict water-related risks such as floods, droughts, and contaminations. 
• Produce technical reports, visualizations, articles and blog content to share findings. 
• Publish forecast performance reports on the company’s blog and explain these to clients.
• Represent BWI at events, conferences and trade shows.
• Contribute to research collaborations by sitting at scientific committees of our partner labs.

Your profiles

• Education:Masters in Hydrology, Water Resources, Agronomy, Geosciences, Geophysics, Civil Engineering, or related field. PhD is a plus.
• Technical Skills:
  • Strong background in statistics, quantitative analysis, data modelling, and hydrological forecasting. 
  • Experience with remote sensing, GIS tools, and hydrological instrumentation. 
  • Solid understanding of information systems and software is preferable.
  • Familiarity with AI/ML applications in environmental sciences is advantageous. 
  • Project management and drive: you are organized, and determined to satisfy stakeholders.
• Soft Skills:
  • Excellent analytical and problem-solving abilities.
  • Strong communication skills, both written and verbal.
  • Comfortable interacting with diverse stakeholders including scientists, engineers, clients, and policymakers.
  • Curious, self-driven, and collaborative mindset.
  • Public speaking skills.
• Language: Fluent in English and in French – both written and spoken (required). 

Frequent travels, in France and globally, will be expected.

Why join us?

• Help tackle one of the world’s most urgent challenges: freshwater availability and hydrological risks. 
• Join a fast-growing, mission-driven company.
• Work in an interdisciplinary, international environment that values curiosity, responsibility, and impact. 
• Enjoy flexible work conditions, engaging offices, and an inspiring team spirit. 

You are expected to build and operate data ingestion and processing pipelines for terabytes of weather and hydrological data, ensuring scalable, reproducible, and production‑grade delivery of model inputs and outputs.

Core responsibilities

• Implement ingestion (batch/streaming), ELT/ETL steps, and data publishing workflows.
• Handle scientific formats (netCDF, GRIB2) and columnar storage (Parquet); optimize I/O and algorithms.
• Design storage with eventual‑consistency patterns (atomic publishes, manifests, versioned paths) and a metadata catalog.
• Partition and parallelize workloads for distributed compute; compact small files and tune for cost/performance.
• Build and run containerized services and orchestrated workflows; ensure observability, retries, idempotency, and runbooks.
• Collaborate with scientists to define data models and validation rules.

Top paradigms & architectural patterns required

• ELT-first with ETL where needed; streaming/micro-batch for low-latency sources
• Data lake + metadata catalogue (object storage), data model design for cataloguing
• Partitioned columnar storage & distributed data-parallel processing
• Idempotent, restartable workflows with orchestration
• Versioned datasets, atomic publish patterns, and catalogue as source of truth
• Observability-driven ops and infra-as-code

Essential tools & technologies

• Python (xarray, netCDF4, pyarrow), PySpark or Dask
• S3-compatible object storage; Parquet format
• PostgreSQL / PostGIS
• Kubernetes + Docker for deployment
• AWS (S3, EKS, EC2) or equivalent cloud; Terraform for IaC

Must-haves

• 3+ years relevant experience building/operating large data pipelines
• Strong software engineering in Python with testing and CI/CD
• Practical experience with partitioning, and parallelism
• Computer science education
• Understanding of architectural patterns in storing & processing large volumes of data
• Humility & eagerness to accept both: full hands-on coding position or technical leadership depending on circumstances
• Clear communication, teamwork, and analytical problem-solving

Nice-to-haves

• Hydrology, meteorology, remote-sensing or space-ground-segment experience
• STAC, GeoTIFF, PostGIS, Numba/Cython performance tuning
• Understanding of low-level subject (memory management, HTTP, S3 implementation)
• Willingness to develop managerial skills

Key Responsibilities:

• Design, develop, and optimize mathematical and physical models for hydrological and environmental applications.
• Implement robust, scalable, and maintainable software solutions to support operational workflows.
• Collaborate with interdisciplinary teams of scientists, engineers, and domain experts to understand requirements and deliver high-impact solutions.
• Perform data analysis and visualization to validate models and interpret results.
• Stay up-to-date with the latest advancements in scientific computing, hydrology, and related fields to integrate cutting-edge techniques into projects.
• Document methodologies, code, and research findings comprehensively and transparently.

Qualifications:

Academic Background:

• Advanced degree (Master’s or Ph.D.) in Mathematics, Physics (Pure or Applied), Computer Science, or a closely related field.
• Strong foundation in numerical methods, differential equations, and computational modeling.

Technical Skills:

• Proficiency in OO Python.
• Experience with software engineering practices, including version control, code reviews, and testing frameworks.
• Familiarity with data analysis tools and libraries (e.g., NumPy, pandas, SciPy) and visualization frameworks (e.g., Matplotlib, Plotly).
• Knowledge of parallel computing and performance optimization is a plus.

Domain Expertise:

• Demonstrated ability to develop and implement mathematical models.
• Background or strong interest in hydrology, environmental science, or fluid dynamics.
• Background or strong interest in neural networks, machine learning, or artificial intelligence.

Soft Skills:

• Strong problem-solving skills and intellectual curiosity.
• Excellent written and verbal communication skills, with the ability to convey complex ideas to diverse audiences.
• Proven ability to work collaboratively in interdisciplinary teams and independently as needed.

Preferred Qualifications:

• Prior experience working in hydrology, water resources, or related scientific domains.
• Familiarity with geospatial data processing and analysis.
• Experience with cloud computing platforms or high-performance computing environments.

What We Offer:

• The opportunity to contribute to meaningful scientific advancements addressing global water challenges.
• A collaborative and intellectually stimulating work environment.
• Professional growth and learning opportunities at the intersection of science and software engineering.
• Competitive compensation and benefits package.

Hiring Process:

• Technical interview with our CTO (can be a visio)
• Technical interview with another team member, if need be (can be a visio)
• Motivational interview with our CEO (telephone or visio)
• Offer
• Deal

Applications will be reviewed on a rolling basis.

Join us in advancing the science of hydrology through innovative software and impactful work!

Key responsibilities:

• 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.

Must-have skills:

• 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.
• GPU scheduling in K8s.
• tensorflow serving | 1password | fastapi | uvicorn.
• Self-hosting LLM + opencode integration.
• Python OOP skills a huge plus.

Logistics & apply:

On-site Toulouse, ideally, or Paris.

Equal Opportunity Statement:

We are committed to diversity and inclusivity.