Flight Test Data Analyst

Structure d'accueil

L’ÉCOLE NORMALE SUPÉRIEURE
Créée en 1794, l'École normale supérieure, membre de l’Université PSL, est un établissement d'enseignement supérieur et de recherche qui recrute sur concours les étudiants les plus talentueux en France et à l'étranger. Établissement d'élite, dont l'activité recouvre l'essentiel des disciplines scientifiques et littéraires, l'ENS-PSL jouit d'un grand prestige international par la qualité de ses étudiants mais aussi par la réputation de ses centres de recherche.

Non-discrimination, ouverture et transparence
Les établissements membres de l'Université PSL s’engagent à soutenir et promouvoir l’égalité, la diversité et l’inclusion au sein de ses communautés. Nous encourageons les candidatures issues de profils variés, que nous veillerons à sélectionner via un processus de recrutement ouvert et transparent.

Missions

Activités principales

Structure d'accueil :
Institut des Textes et Manuscrits Modernes (UMR8132) – Équipe Archivos. Projet ANR CARTAS – Pablo Picasso en toutes lettres

Catégorie d'emploi :
A - Ingénieur d'études

ENVIRONNEMENT DE TRAVAIL
L’Équipe Archivos de l’ITEM (UMR8132), recrute un ingénieur d’études pour participer à la collecte, la structuration, et l’intégration des métadonnées liées à la correspondance reçue par Pablo Picasso, dans le cadre du projet ANR CARTAS (2025–2029). Ce projet interdisciplinaire réunit chercheurs en humanités, juristes et spécialistes du traitement automatique des données afin de cartographier et analyser les réseaux culturels autour de Picasso, à partir d’un corpus de plus de 30 000 lettres conservées au Musée national Picasso Paris.

MISSION PRINCIPALE
L’ingénieur recruté aura pour mission principale de participer à la collecte, la modélisation, la normalisation et l’enrichissement des métadonnées du corpus épistolaire de Pablo Picasso. Il/elle contribuera également à l’intégration des données dans le lac de données qui sera développé, à des fins d’analyse et de visualisation des réseaux culturels.

ACTIVITÉS PRINCIPALES

• Exploration, analyse et structuration des métadonnées issues du corpus de correspondances
• Participation à l’alimentation de la base de métadonnées partagée
• Élaboration de mappings entre métadonnées hétérogènes et formats standards (TEI, Dublin Core, etc.)
• Contribution à la modélisation de liens sémantiques entre entités (correspondants, œuvres, événements)
• Co-rédaction de la documentation technique et du plan de gestion des données du projet

SPECIFICITES DU POSTE

• Travail en lien avec plusieurs partenaires institutionnels (MNPP, Huma-Num, Universités françaises et étrangères)
• Participation à des ateliers techniques et à des réunions de coordination internationales
• Encadrement possible de stagiaires ou d’assistants de recherche
• Déplacements occasionnels en France et à l’étranger
• Travail à mi-temps

CHAMPS DES RELATIONS
Internes :
Équipe Archivos, chercheurs de l’ITEM, département informatique ENS-PSL

Externes
: Musée national Picasso Paris, consortium du projet CARTAS, consortium ARIANE de l’infrastructure Huma-Num

Profil du candidat

Savoirs et compétences attendus

COMPÉTENCES ATTENDUES
Diplôme :
Bac+3 en Humanités numériques, Traitement automatique des données, ou équivalent

Langue
: Niveau C (CECRL) en espagnol

Expérience professionnelle :
Expérience souhaitée dans un projet de recherche impliquant des données patrimoniales et/ou textuelles

Connaissances

• Métadonnées en SHS : TEI, Dublin Core, MODS, vocabulaire contrôlé
• Structuration et interopérabilité des données
• Normes FAIR
• Humanités numériques, XML, TEI, RDF, JSON
• Langues : espagnol, portugais, anglais

Compétences Techniques

• Outils : XSLT, SPARQL, Python, Git, gestion collaborative de documentation, OpenRefine
• Bases de données (relationnelles ou documentaires), gestion de formats hétérogènes
• Construction de mappings, modélisation sémantique
• Expérience avec des plateformes comme Nakala, MyNkl, ou outils FAIR

Compétences Comportementales

• Rigueur, autonomie, sens de l’organisation
• Goût du travail en équipe interdisciplinaire et international
• Qualités rédactionnelles et de communication
• Intérêt pour l’histoire de l’art, les Lettres et les humanités de façon général

Cadre D’emploi
Niveau d’emploi : A - Ingénieur d'études

Poste à pourvoir dans les meilleurs délais

Poste ouvert : Aux contractuels CDD de 12 mois

Quotité de travail : 50% - 18h45/semaine

Lieu de travail : 45 rue d'Ulm - 75005 Paris

Rémunération : Selon grille et expérience

Qualite De Vie a L’ens-psl
En rejoignant l’ENS-PSL, selon le statut et les activités exercées, vous pourrez notamment bénéficier :

• Jusqu’à 49 jours de congés par an (dont RTT) pour un temps complet
• Jusqu’à 2 jours de télétravail par semaine
• Large offre de formations professionnelles via une école interne
• Accès aux services du campus (restauration, bibliothèques, activités sportives, etc.)
• Avantages sociaux : 75 % du titre de transport, allocation mobilité durable, complémentaire santé etc.

POURQUOI NOUS REJOINDRE ?

• Pour intégrer un établissement handi-accueillant, engagé pour la diversité, la mixité et l’égalité des chances.
• Pour contribuer au rayonnement d’un établissement d’excellence, impliqué dans des projets stratégiques, dans un environnement stimulant et collaboratif.

COMMENT NOUS REJOINDRE ? :
Envoyer CV et lettre de motivation via le bouton « Postuler à cette offre ».

Diplôme et expérience professionnelle

Bac+3

Are you looking for a new challenge?

Fancy helping us shape the future of motor insurance?

Prima could be the place for you.

Since 2015, we’ve been using our love of data and tech to rethink motor insurance and bring drivers a great experience at a great price. Our story began in Italy, where we’ve quickly become the number one online motor insurance provider. In fact, we’re trusted by over 5 million drivers. And now we’re expanding to help millions more drivers in the UK and Spain.

To help fuel that growth, we need a
Software/Data Engineer
to join our
Engineering team.
This team is the beating heart of Prima.

You’ll be joining over 300 engineers across software development, infrastructure, operations and security. Fueled by curiosity, experimentation and collaboration, you’ll help deliver scalable, impactful solutions that shape the future of insurance.

Excited to make an impact? Here are the details
You’ll be joining our pricing and underwriting domain to bridge the gap between machine learning/data science and engineering. You will help build, publish, and maintain our complex data products and pipelines, key elements that have a significant impact on the company’s growth.

What You’ll Do

• Shaping the architecture of data products designed for data analytics and data science specifically focusing on use cases like forecasting, feature engineering, customer behaviour, and integration of new data sources.
• Leading the way in data transformation by setting up best practices in areas like Data modelling, performance optimisation, Data Governance etc, ensuring that the data used within Prima is consistent, available and reliable.
• Build reusable technology that enables teams to ingest, store, transform, and serve their own data products.
• Engaging with data scientists and machine learning engineers to explore the product landscape and refine data requirements for enhanced data infrastructure.
• Embrace continuous learning and experimentation to stay updated on emerging technologies, from testing open source tools to engaging in community-building activities like Meetups. Your passion for staying at the forefront of the field will drive your journey.

What We’re Looking For

• Expert in batch, distributed data processing and near real-time streaming data pipelines with technologies like Kafka, Flink, Spark etc. Experience in Databricks is a plus.
• Experience in Data Lake / Big Data Analytics platform implementation with cloud based solution; AWS preferred.
• Proficient in Python programming and software engineering best practices.
• Expertise with RDBMS, Data Warehousing, Data Modelling with relational SQL (Redshift, PostgreSQL) and NoSQL databases.
• Proficiency in DevOps, CI/CD pipeline management, and expertise in infrastructure as Code (IaC) deployment industry-best practices.

Nice-to-Have

• Hands-on experience in Data Quality and Data Governance techniques.
• Knowledge on MLOps and Feature engineering.
• Exposure to common data analysis and ML technologies such as on scikit-learn, pandas, NumPy, XGBoost, LightGBM.
• Exposure to tools like Apache Oozie, Apache Airflow.

€55,000 - €85,000 a year

Why you’ll love it here
We want to make Prima a happy and empowering place to work. So if you decide to join us, you can expect plenty of perks.

🤸 Work Your Way:
Enjoy full flexibility – work from home, the office or a mix of both. Plus, work from anywhere for up to 30 days a year.

🏁 Grow with us:
We may move fast at Prima, but we move together. Get access to learning resources, mentorship and a growth plan tailored to you.

🌈 Thrive and perform:
Your best work begins when you feel your best. Enjoy private healthcare, gym discounts, wellbeing programs and mental health support.

Think you’re a match? Apply now.

At Prima, we celebrate uniqueness. If you don’t meet every requirement but are passionate about this role, we still want to hear from you. Innovation thrives on diverse perspectives.

Prima is proud to be an equal opportunity employer. Need accommodations during the process? Email us at accessible.recruiting@prima.it. Let’s build the future of insurance, together.

Job Location
WARSAW DOWNTOWN OFFICE

Job Description
We are looking for a Site Reliability Engineer who builds things — AI agents, automations, and tools that keep our enterprise data pipelines running at scale. If you write production-quality code and are excited by the challenge of building AI-powered systems, we want to hear from you.

Key responsibilities:

• Build LLM-enabled AI agents that detect, classify, and diagnose issues in data pipelines — replacing manual investigation with automated reasoning and self-healing workflows.
• Collaborate with engineering teams to embed observability, reliability, and resilience from design through to production — not add it after things break.
• Build proactive data quality systems — automated checks that validate data as it flows through pipelines, catching issues before they reach consumers.
• Build logging and monitoring tooling that automatically surfaces issues before they impact downstream users — making failures visible and debuggable.
• Investigate failures, identify root causes, and turn learnings into better systems.

Job Qualifications

• 2+ years of experience in Software Engineering or Data Engineering.
• Experience building ETL/ELT data pipelines.
• Strong software development skills in Python — you write production-quality code.
• Practical experience building with LLMs or AI agents; you have shipped something that uses generative AI in a production or near-production context.
• Working knowledge of cloud services (Azure preferred), including Infrastructure as a Code (e.g. Terraform).
• Experience building logging systems in production.

We offer

• P&G-sized projects and access to world leading IT partners and technologies from Day 1.
• Wide range of self-development possibilities (training and certifications paths).
• Competitive starting salary and benefits program (private health care, P&G stock, saving plans, sport cards).
• Regular salary increases and possible promotions - in line with your results and performance.
• Opportunity to change role every few years to be in the best place for you and best for P&G.

At Procter & Gamble we embrace a
hybrid work model
that combines the flexibility of remote work with the collaborative benefits of in-office engagement. Employees can enjoy the option to work from home two days a week while also spending time in the office to foster teamwork and enhance communication.

Watch this video to learn more about our full recruiting process: https://www.youtube.com/watch?v\=0bicvbpy0gI

Kindly be advised that at P&G, employment is exclusively extended on the basis of an "Umowa o Pracę" (Full-time Employment Contract). Apply only if you agree to these conditions.

About Us
We produce globally recognized brands and we grow the best business leaders in the industry. With a portfolio of trusted brands as diverse as ours, it is paramount our leaders can lead with courage the vast array of brands, categories and functions. We serve consumers around the world with one of the strongest portfolios of trusted, quality, leadership brands, including Always®, Ariel®, Gillette®, Head & Shoulders®, Herbal Essences®, Oral-B®, Pampers®, Pantene®, Tampax® and more. Our community includes operations in approximately 70 countries worldwide.

Visit http://www.pg.com to know more.

We are an equal opportunity employer and value diversity at our company. We do not discriminate against individuals on the basis of race, color, gender, age, national origin, religion, sexual orientation, gender identity or expression, marital status, citizenship, disability, HIV/AIDS status, or any other legally protected factor.

Job Schedule
Full time

Job Number
R000157214

Job Segmentation
Experienced Professionals

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Product Data Engineer based in Switzerland.
This is a senior data engineering opportunity focused on building customer-facing data products from complex, large-scale, and often unstructured data.

You will join a specialized Data Insights team responsible for turning raw signals into reliable, valuable intelligence that powers core product experiences.

Your work will span data processing, ETL/ELT, orchestration, AI-assisted search, LLM-powered capabilities, and scalable data architectures.

You will own high-impact projects end-to-end, from initial idea and architecture through production launch, iteration, and optimization.

The role combines hands-on engineering with strong product thinking, requiring you to balance quality, performance, cost, and customer value.

You will work in a remote-first environment with high autonomy, fast feedback loops, pair programming, and limited unnecessary meetings.

This is an opportunity to shape the data backbone behind innovative customer-facing products while helping define how AI and large-scale data processing are used in production.

Accountabilities
You will take ownership of complex data products and systems, working across engineering, AI, and product capabilities to deliver reliable and scalable customer-facing solutions.

• Design, build, and operate data products that transform raw social and public data into consistent, customer-facing insights.
• Develop large-scale ETL/ELT pipelines and data processing systems using Spark, with PySpark as a preferred technology.
• Work with unstructured and complex datasets to extract meaningful information and create reliable data products.
• Own projects end-to-end, from discovery, planning, and scoping through architecture, implementation, production release, and iteration.
• Build and improve systems that generate insights such as creator locations, demographics, interests, brand collaborations, and other data-driven intelligence.
• Contribute to the development of AI-assisted search, recommendations, and other intelligent product capabilities using LLMs and embeddings.
• Build and operate LLM-powered and agentic features in production environments.
• Design reliable workflows and orchestration processes using tools such as Airflow or AWS Step Functions.
• Work across AWS and GCP infrastructure to support scalable data processing, storage, and AI workloads.
• Monitor system performance, reliability, data quality, and operational costs as data volumes and product usage grow.
• Make informed trade-offs between LLM capability, latency, reliability, and cost.
• Collaborate with data engineers, backend engineers, and other technical stakeholders through pair programming, code reviews, and rapid feedback cycles.
• Contribute to system architecture and technical decisions while maintaining high standards for code quality, scalability, and maintainability.
• Help evolve data systems and customer-facing capabilities as product requirements and technologies change.

Requirements
The ideal candidate is a hands-on senior data engineer who combines strong large-scale data processing expertise with product ownership, modern AI capabilities, and a pragmatic approach to system design.

• Strong professional knowledge of Apache Spark, with PySpark preferred; experience with Scala or Databricks is also valuable.
• Proven experience building ETL/ELT pipelines and processing data at significant scale.
• Comfortable working with unstructured, messy, and complex datasets.
• Hands-on experience with workflow orchestration tools such as Airflow or AWS Step Functions.
• Familiarity with the AWS ecosystem, particularly services such as Glue and EMR.
• Demonstrated ability to ship complete production features from idea and scoping through architecture, implementation, release, and iteration.
• Hands-on experience building and deploying agentic or LLM-powered features in production.
• Practical understanding of LLM trade-offs involving cost, latency, performance, and capability.
• Strong system design and software engineering fundamentals.
• High attention to code quality, reliability, scalability, and maintainability.
• Experience working autonomously and taking ownership of complex technical problems.
• Strong communication skills and ability to provide direct, constructive feedback within a collaborative engineering environment.
• Based in Europe with significant working-hours overlap with EET/Tallinn time.
• Experience with AI/ML tools and LLM technologies is a plus.
• Familiarity with GCP, particularly Vertex AI, is advantageous.
• Experience with lakehouse technologies such as Apache Iceberg is beneficial.
• Experience using Pulumi or Terraform for infrastructure as code is a plus.
• Familiarity with Node.js and TypeScript is advantageous.
• Understanding of AWS cost mechanics and how infrastructure spending changes with scale is beneficial.
• Interest in the creator economy and social data products is a plus.
• Experience should ideally extend beyond analytics, BI, dashboards, or internal reporting into production data systems and customer-facing applications.

Benefits

• Fully remote position with the flexibility to work from anywhere in Europe.
• Annual salary range of €90,000–€140,000, depending on location, employment type, skills, and experience.
• Stock options in addition to salary, with a significant equity component.
• Unlimited paid vacation.
• Flexible working hours and an async-friendly culture.
• High level of ownership with low bureaucracy and minimal unnecessary meetings.
• Personal development support covering courses, books, conferences, and other learning opportunities.
• Regular team offsites and opportunities to connect with colleagues in person.
• Opportunity to work on large-scale data products with direct customer impact.
• Exposure to modern technologies across AWS, GCP, Spark, Airflow, LLMs, AI agents, lakehouse architectures, and infrastructure as code.
• Opportunity to influence AI-assisted search, recommendations, and intelligent data products from the early stages.
• Collaborative environment with experienced data and backend engineers and strong emphasis on autonomy, feedback, and technical ownership.

How Jobgether Works
We use an
AI-powered matching process
to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.